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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
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<meta http-equiv="Content-Type" content="text/html" charset="utf-8" />
<title>Meng Jiang - University of Notre Dame</title>
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<li class="yuimenuitem first-of-type"><a class="yuimenuitemlabel" href="lab.html"><b>DM2 Lab</b></a></li>
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<li class="yuimenuitem first-of-type"><a class="yuimenuitemlabel" href="pubs.html">Publications</a></li>
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<h1>Publications</h1>
In chronological order | <a href="https://scholar.google.com/citations?user=LZIPfCkAAAAJ">Google Scholar</a> | <a href="http://dblp.uni-trier.de/pers/hd/j/Jiang_0001:Meng">DBLP</a>
<h2>Conference Papers</h2>
<ul>
<b>2026</b>
<li class="O">[<b>C140</b>] <a href="https://arxiv.org/abs/2508.04660">Composing Policy Gradients and Prompt Optimization for Language Model Programs</a>
by N. Ziems, D. Soylu, L. Agrawal, I. Miller, L. Lai, C. Qian, K. Song, <b>M. Jiang</b>, D. Klein, M. Zaharia, K. D’Oosterlinck, C. Potts, O. Khattab.
<i>ACM Conference on AI and Agentic Systems (<b>CAIS</b>)</i>, 2026.
</li>
<li class="O">[<b>C139</b>] <a href="#">Dossier: Deep Research via Ledger-Driven Branching Search and Query Encoding Learning</a>
by O. Chabra, N. Ziems, <b>M. Jiang</b>, O. Khattab, H. Balakrishnan.
<i>ACM Conference on AI and Agentic Systems (<b>CAIS</b>)</i>, 2026.
</li>
<li class="O">[<b>C138</b>] <a href="https://arxiv.org/abs/2502.08893">Uncovering Disparities in Rideshare Drivers Earning and Work Patterns: A Case Study of Chicago</a>
by H. Dang, Y. Lu, J. Spicer, T. Kay, D. Yang, Y. Yang, J. Brockman, <b>M. Jiang</b>, T. Li.
<i>ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (<b>CSCW</b>)</i>, 2026.
</li>
<li class="O">[<b>C137</b>] <a href="https://arxiv.org/abs/2510.23477">MMTutorBench: The First Multimodal Benchmark for AI Math Tutoring</a>
by T. Yang, S. Guo, M. Jia, J. Su, Y. Liu, Z. Zhang, <b>M. Jiang</b>.
<i>Annual Meeting of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2026.
</li>
<li class="O">[<b>C136</b>] <a href="https://arxiv.org/abs/2510.16282">Instant Personalized Large Language Model Adaptation via Hypernetwork</a>
by Z. Tan, Z. Zhang, H. Wen, Z. Li, R. Zhang, P. Chen, F. Mo, Z. Liu, Q. Zeng, Q. Yin, <b>M. Jiang</b>.
<i>Annual Meeting of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2026.
</li>
<li class="O">[<b>C135</b>] <a href="#">Mitigating Lost in Multi-turn Conversation via Curriculum RL with Verifiable Accuracy and Abstention Rewards</a>
by M. Li, P. Chen, Z. Zhang, T. Yang, X. Zhang, H. Li, T. Cao, M. Zeng, Z. Wu, <b>M. Jiang</b>, H. Li, L. Li, B. Yin.
<i>Annual Meeting of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2026.
</li>
<li class="O">[<b>C134</b>] <a href="https://arxiv.org/abs/2510.14738">AutoRubric: Rubric-Based Generative Rewards for Faithful Multimodal Reasoning</a>
by M. Jia, Z. Zhang, I. Cases, F. Liu, <b>M. Jiang</b>, P. Qi.
<i>Findings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2026.
</li>
<li class="O">[<b>C133</b>] <a href="#">Do LLMs Catch Their Own Mistakes? A Comprehensive Benchmark for Reflective Tool Use LLMs</a>
by Z. Liu, L. Xiao, Y. Li, H. Yun, L. Li, C. Zhang, <b>M. Jiang</b>.
<i>Findings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2026.
</li>
<li class="O">[<b>C132</b>] <a href="https://arxiv.org/abs/2601.06757">MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues</a>
by Z. Liu, D. Kim, Y. Wan, X. Yuan, Z. Tan, F. Mo, <b>M. Jiang</b>.
<i>Findings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2026.
</li>
<li class="O">[<b>C131</b>] <a href="https://arxiv.org/abs/2601.13115">Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning</a>
by F. Mo, Y. Gao, S. Li, H. Zeng, X. Liu, Z. Tan, X. Li, J. Chen, D. Wang, <b>M. Jiang</b>.
<i>Findings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2026.
</li>
<li class="O">[<b>C130</b>] <a href="https://arxiv.org/abs/2601.14896">Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation</a>
by R. Qi, F. Mo, Y. Chen, X. Zhang, S. Wang, H. Li, J. Xu, <b>M. Jiang</b>, J. Nie, K. Huang.
<i>Findings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2026.
</li>
<li class="O">[<b>C129</b>] <a href="https://arxiv.org/abs/2406.16173">Crepe: A Mobile Screen Data Collector Using Graph Query</a>
by Y. Lu, M. Chen, Q. Zhao, V. Cox, Y. Yang <b>M. Jiang</b>, J. Brockman, T. Kay, T. Li.
<i>ACM CHI conference on Human Factors in Computing Systems (<b>CHI</b>)</i>, 2026. (<b style="color:red">Honourable Mention Award</b>)
</li>
<li class="O">[<b>C128</b>] <a href="https://arxiv.org/abs/2510.08744">Graph Diffusion Transformers are In-Context Molecular Designers</a>
by G. Liu, J. Chen, Y. Zhu, M. Sun, T. Luo, N.V., Chawla, <b>M. Jiang</b>.
<i>International Conference on Learning Representations (<b>ICLR</b>)</i>, 2026.
</li>
<li class="O">[<b>C127</b>] <a href="https://arxiv.org/abs/2509.23362">Dual-Space Smoothness for Robust and Balanced LLM Unlearning</a>
by H. Yan, Z. Liu, <b>M. Jiang</b>.
<i>International Conference on Learning Representations (<b>ICLR</b>)</i>, 2026.
</li>
<li class="O">[<b>C126</b>] <a href="https://arxiv.org/abs/2507.19457">GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning</a>
by L.A. Agrawal, S. Tan, D. Soylu, N. Ziems, R. Khare, K. Opsahl-Ong, A. Singhvi, H. Shandilya, M.J. Ryan, <b>M. Jiang</b>, C. Potts, K. Sen, A. Dimakis, I. Stoica, D. Klein, M. Zaharia, O. Khattab.
<i>International Conference on Learning Representations (<b>ICLR</b>)</i>, 2026.
</li>
<li class="O">[<b>C125</b>] <a href="https://arxiv.org/abs/2504.19406">Context Selection and Rewriting for Video-based Educational Question Generation</a>
by M. Yu, B. Nguyen, O. Zino, <b>M. Jiang</b>.
<i>Symposium on Educational Advances in Artificial Intelligence (<b>EAAI</b>)</i>, 2026.
</li>
<li class="O">[<b>C124</b>] <a href="#">High-performance Polymeric Gas Separation Membrane Designed by Explainable Graph Augmented and Imbalanced Machine Learning</a>
by T. Luo, J. Xu, A. Suleiman, G. Liu, R. Zhang, <b>M. Jiang</b>, R. Guo.
<i>International Symposium Frontiers in Polymer Science</i>, 2026.
</li>
<b>2025</b>
<li class="O">[<b>C123</b>] <a href="https://arxiv.org/abs/2505.10726">Learning Repetition-Invariant Representations for Polymer Informatics</a>
by Y. Zhu, G. Liu, E. Inae, T. Luo, <b>M. Jiang</b>.
<i>Annual Conference on Neural Information Processing Systems (<b>NeurIPS</b>)</i>, 2025.
</li>
<li class="O">[<b>C122</b>] <a href="https://arxiv.org/abs/2507.22543">Pre-trained Models Perform the Best When Token Distributions Follow Zipf's Law</a>
by Y. He, Q. Zeng, <b>M. Jiang</b>.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2025.
</li>
<li class="O">[<b>C121</b>] <a href="#">Improving Large Language Models Function Calling and Interpretability via Guided-Structured Templates</a>
by H. Dang, T. Liu, Z. Wu, J. Yang, H. Jiang, T. Yang, P. Chen, Z. Wang, H. Wang, H. Li, B. Yin, <b>M. Jiang</b>.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2025.
</li>
<li class="O">[<b>C120</b>] <a href="https://www.cs.odu.edu/~jwu/downloads/pubs/soos-2025-ht/soos-2025-ht.pdf">Can LLMs Beat Humans on Discerning Human-written and LLM-generated Science News?</a>
by D. Soós, <b>M. Jiang</b>, J. Wu.
<i>ACM Conference on Hypertext and Social Media (<b>HT</b>)</i>, 2025.
</li>
<li class="O">[<b>C119</b>] <a href="https://arxiv.org/abs/2408.09070">CodeTaxo: Enhancing Taxonomy Expansion with Limited Examples via Code Language Prompts</a>
by Q. Zeng, Y. Bai, Z. Tan, Z. Wu, S. Feng, <b>M. Jiang</b>.
Findings of <i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2025.
</li>
<li class="O">[<b>C118</b>] <a href="https://arxiv.org/abs/2503.05888">QG-SMS: Enhancing Test Item Analysis via Student Modeling and Simulation</a>
by B. Nguyen, T. Du, M. Yu, L. Angrave, <b>M. Jiang</b>.
<i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2025.
</li>
<li class="O">[<b>C117</b>] <a href="https://arxiv.org/abs/2503.15354">Optimizing Decomposition for Optimal Claim Verification</a>
by Y. Lu, N. Ziems, H. Dang, <b>M. Jiang</b>.
<i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2025.
</li>
<li class="O">[<b>C116</b>] <a href="https://aclanthology.org/2025.acl-long.295/">Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models</a>
by Z. Liu, G. Dou, X. Yuan, C. Zhang, Z. Tan, <b>M. Jiang</b>.
<i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2025.
</li>
<li class="O">[<b>C115</b>] <a href="https://aclanthology.org/2025.acl-long.305/">Disentangling Biased Knowledge from Reasoning in Large Language Models via Machine Unlearning</a>
by Z. Liu, S. Maharjan, F. Wu, R. Parikh, B. Bayar, S. Sengamedu, <b>M. Jiang</b>.
<i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2025.
</li>
<li class="O">[<b>C114</b>] <a href="https://www.arxiv.org/abs/2506.04463">Aligning Large Language Models with Implicit Preferences from User-Generated Content</a>
by Z. Tan, Z. Li, T. Liu, H. Wang, H. Yun, M. Zeng, P. Chen, Z. Zhang, Y. Gao, R. Wang, P. Nigam, B. Yin, <b>M. Jiang</b>.
<i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2025.
</li>
<li class="O">[<b>C113</b>] <a href="https://arxiv.org/abs/2410.12934">Enhancing Mathematical Reasoning in LLMs by Stepwise Correction</a>
by Z. Wu, Q. Zeng, Z. Zhang, Z. Tan, C. Shen, <b>M. Jiang</b>.
<i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2025.
</li>
<li class="O">[<b>C112</b>] <a href="https://aclanthology.org/2025.acl-long.344/">UniConv: Unifying Retrieval and Response Generation for Large Language Model in Conversation</a>
by F. Mo, Y. Gao, C. Meng, X. Liu, Z. Wu, K. Mao, Z. Wang, P. Chen, Z. Li, X. Li, B. Yin, <b>M. Jiang</b>.
<i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2025.
</li>
<li class="O">[<b>C111</b>] <a href="https://aclanthology.org/2025.acl-long.404/">Cross-Lingual Pitfalls: Automatic Probing Cross-Lingual Weakness of Multilingual Large Language Models</a>
by Z. Xu, Y. Wang, Y. Huang, X. Chen, J. Zhao, <b>M. Jiang</b>, X. Zhang.
<i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2025.
</li>
<li class="O">[<b>C110</b>] <a href="https://arxiv.org/abs/2506.17787v1">Incorporating Rather Than Eliminating: Achieving Fairness for Skin Disease Diagnosis Through Group-Specific Experts</a>
by G. Xu, Y. Duan, Z. Liu, X. Li, <b>M. Jiang</b>, M. Lemmon, W. Jin, Y. Shi.
<i>Medical Image Computing and Computer Assisted Intervention (<b>MICCAI</b>)</i>, 2025.
</li>
<li class="O">[<b>C109</b>] <a href="https://arxiv.org/abs/2410.22108">Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench</a>
by Z. Liu, G. Dou, M. Jia, Z. Tan, Q. Zeng, Y. Yuan, <b>M. Jiang</b>.
<i>Annual Conference of the North American Chapter of the Association for Computational Linguistics (<b>NAACL</b>)</i>, 2025.
[<a href="https://aclanthology.org/2025.naacl-long.207/">DOI</a>]
</li>
<li class="O">[<b>C108</b>] <a href="https://arxiv.org/abs/2502.08745">IHEval: Evaluating Language Models on Following the Instruction Hierarchy</a>
by Z. Zhang, S. Li, Z. Zhang, X. Liu, H. Jiang, X. Tang, Y. Gao, Z. Li, H. Wang, Z. Tan, Y. Li, Q. Yin, B. Yin, <b>M. Jiang</b>.
<i>Annual Conference of the North American Chapter of the Association for Computational Linguistics (<b>NAACL</b>)</i>, 2025.
[<a href="https://aclanthology.org/2025.naacl-long.425/">DOI</a>]
</li>
<li class="O">[<b>C107</b>] <a href="https://arxiv.org/abs/2410.14179">MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart Problems</a>
by Z. Zhu, M. Jia, Z. Zhang, L. Li, <b>M. Jiang</b>.
<i>Annual Conference of the North American Chapter of the Association for Computational Linguistics (<b>NAACL</b>)</i>, 2025.
[<a href="https://aclanthology.org/2025.naacl-long.566/">DOI</a>]
</li>
<li class="O">[<b>C106</b>] <a href="https://arxiv.org/abs/2407.09007">Benchmarking Language Model Creativity: A Case Study on Code Generation</a>
by Y. Lu, D. Wang, T. Li, D. Jiang, S. Khudanpur, <b>M. Jiang</b>, D. Khashabi.
<i>Annual Conference of the North American Chapter of the Association for Computational Linguistics (<b>NAACL</b>)</i>, 2025.
[<a href="https://aclanthology.org/2025.naacl-long.141/">DOI</a>]
</li>
<li class="O">[<b>C105</b>] <a href="https://arxiv.org/abs/2410.04223">Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning</a>
by G. Liu, M. Sun, W. Matusik, <b>M. Jiang</b>, J. Chen.
<i>International Conference on Learning Representations (<b>ICLR</b>)</i>, 2025.
</li>
<li class="O">[<b>C104</b>] <a href="https://arxiv.org/abs/2406.12056">Learning Molecular Representation in a Cell</a>
by G. Liu, S. Seal, J. Arevalo, Z. Liang, A. Carpenter, <b>M. Jiang</b>, S. Singh.
<i>International Conference on Learning Representations (<b>ICLR</b>)</i>, 2025.
</li>
<li class="O">[<b>C103</b>] <a href="https://arxiv.org/abs/2410.20266">Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Tasks</a>
by A. Szymanski, N. Ziems, T. Li, <b>M. Jiang</b>, R. Metoyer.
<i>ACM Conference on Intelligent User Interfaces (<b>IUI</b>)</i>, 2025.
[<a href="https://doi.org/10.1145/3708359.3712091">DOI</a>]
</li>
<li class="O">[<b>C102</b>] <a href="https://dl.acm.org/doi/10.1145/3690624.3709267">Learning Attribute as Explicit Relation for Sequential Recommendation</a>
by G. Liu, F. Yang, Y. Jiao, A.B. Garakani, T. Tong, Y. Gao, <b>M. Jiang</b>.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2025.
[<a href="https://doi.org/10.1145/3690624.3709267">DOI</a>]
</li>
<b>2024</b>
<li class="O">[<b>C101</b>] <a href="https://arxiv.org/abs/2309.04589">Motif-aware Attribute Masking for Molecular Graph Pre-training</a>
by E. Inae, G. Liu, <b>M. Jiang</b>.
<i>Learning on Graphs Conference (<b>LoG</b>)</i>, 2024.
</li>
<li class="O">[<b>C100</b>] <a href="https://www.aicrowd.com/challenges/amazon-kdd-cup-2024-multi-task-online-shopping-challenge-for-llms">ShopBench: A Massive Multi-Task Online Shopping Benchmark for Large Language Models</a>
by Y. Jin, and many others including <b>M. Jiang</b>.
<i>Conference on Neural Information Processing Systems (<b>NeurIPS</b>)</i>, 2024. (Dataset and Benchmark track)
</li>
<li class="O">[<b>C99</b>] <a href="https://arxiv.org/abs/2401.13858">Graph Diffusion Transformer for Multi-Conditional Molecular Generation</a>
by G. Liu, J. Xu, T. Luo, <b>M. Jiang</b>.
<i>Conference on Neural Information Processing Systems (<b>NeurIPS</b>)</i>, 2024. (Oral)
[<a href="https://github.com/liugangcode/Graph-DiT">project</a>]
</li>
<li class="O">[<b>C98</b>] <a href="https://arxiv.org/abs/2405.14092">Large Language Models Can Self-Correct with Key Condition Verification</a>
by Z. Wu, Q. Zeng, Z. Zhang, Z. Tan, C. Shen, <b>M. Jiang</b>.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.emnlp-main.714">DOI</a>]
</li>
<li class="O">[<b>C97</b>] <a href="https://arxiv.org/abs/2406.10471">Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts</a>
by Z. Tan, Z. Liu, <b>M. Jiang</b>.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.emnlp-main.371">DOI</a>]
</li>
<li class="O">[<b>C96</b>] <a href="https://arxiv.org/abs/2402.04401">Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning</a>
by Z. Tan, Q. Zeng, Y. Tian, Z. Liu, B. Yin, <b>M. Jiang</b>.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.emnlp-main.372">DOI</a>]
</li>
<li class="O">[<b>C95</b>] <a href="https://arxiv.org/abs/2406.12050">Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning</a>
by Z. Zhang, T. Ge, Z. Liang, W. Yu, D. Yu, M. Jia, D. Yu, <b>M. Jiang</b>.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.emnlp-main.817">DOI</a>]
</li>
<li class="O">[<b>C94</b>] <a href="https://aclanthology.org/2024.emnlp-main.1144/">RAt: Injecting Implicit Bias for Text-To-Image Prompt Refinement Models</a>
by Z. Kou, S. Pei, <b>M. Jiang</b>, X. Zhang.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.emnlp-main.1144">DOI</a>]
</li>
<li class="O">[<b>C93</b>] <a href="https://arxiv.org/abs/2403.12242">Reference-based Metrics Disprove Themselves in Question Generation</a>
by B. Nguyen, M. Yu, Y. Huang, <b>M. Jiang</b>.
Findings of <i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.findings-emnlp.798">DOI</a>]
</li>
<li class="O">[<b>C92</b>] <a href="https://arxiv.org/abs/2410.06089">TOWER: Tree Organized Weighting for Evaluating Complex Instructions</a>
by N. Ziems, Z. Zhang, <b>M. Jiang</b>.
Findings of <i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.findings-emnlp.809">DOI</a>]
</li>
<li class="O">[<b>C91</b>] <a href="https://arxiv.org/abs/2402.07386">Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples</a>
by Q. Zeng, Y. Bai, Z. Tan, S. Feng, Z. Liang, Z. Zhang, <b>M. Jiang</b>.
<i>ACM International Conference on Information and Knowledge Management (<b>CIKM</b>)</i>, 2024.
[<a href="https://doi.org/10.1145/3627673.3679608">DOI</a>]
</li>
<li class="O">[<b>C90</b>] <a href="https://dl.acm.org/doi/10.1145/3627673.3679737">FaDE: A Face Segment Driven Identity Anonymization Framework For Fair Face Recognition</a>
by Z. Kou, Y. Tian, <b>M. Jiang</b>, X. Zhang.
<i>ACM International Conference on Information and Knowledge Management (<b>CIKM</b>)</i>, 2024.
[<a href="https://doi.org/10.1145/3627673.3679737">DOI</a>]
</li>
<li class="O">[<b>C89</b>] <a href="https://arxiv.org/abs/2311.08711">PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning</a>
by Z. Zhang, D. Lee, Y. Fang, W. Yu, M. Jia, <b>M. Jiang</b>.
<i>Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.acl-long.379">DOI</a>]
</li>
<li class="O">[<b>C88</b>] <a href="https://arxiv.org/abs/2402.10058">Towards Safer Large Language Models through Machine Unlearning</a>
by Z. Liu, G. Dou, Z. Tan, Y. Tian, <b>M. Jiang</b>.
<i>Findings of Annual Meetings of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.findings-acl.107">DOI</a>]
</li>
<li class="O">[<b>C87</b>] <a href="https://arxiv.org/abs/2401.05561">TrustLLM: Trustworthiness in Large Language Models</a>
by L. Sun, and many others including <b>M. Jiang</b>.
<i>International Conference on Machine Learning (<b>ICML</b>)</i>, 2024. (Position paper)
</li>
<li class="O">[<b>C86</b>] <a href="https://arxiv.org/abs/2311.12275">Enabling On-Device Self-Supervised LLM Personalization with Selective Synthetic Data</a>
by R. Qin, J. Xia, Z. Jia, <b>M. Jiang</b>, A. Abbasi, P. Zhou, J. Hu, Y. Shi.
<i>Design Automation Conference (<b>DAC</b>)</i>, 2024.
</li>
<li class="O">[<b>C85</b>] <a href="https://arxiv.org/abs/2403.12744">Instructing Large Language Models to Identify and Ignore Irrelevant Conditions</a>
by Z. Wu, <b>M. Jiang</b>, C. Shen.
<i>Annual Conference of the North American Chapter of the Association for Computational Linguistics (<b>NAACL</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.naacl-long.379">DOI</a>]
[<a href="https://wzy6642.github.io/I3C.github.io/">project</a>]
</li>
<li class="O">[<b>C84</b>] <a href="https://arxiv.org/abs/2402.10670">OpenFMNav: Towards Open-Set Zero-Shot Object Navigation via Vision-Language Foundation Models</a>
by Y. Kuang, H. Lin, <b>M. Jiang</b>.
Findings of <i>Annual Conference of the North American Chapter of the Association for Computational Linguistics (<b>NAACL</b>)</i>, 2024.
[<a href="https://doi.org/10.18653/v1/2024.findings-naacl.24">DOI</a>]
[<a href="https://yxkryptonite.github.io/OpenFMNav/">project</a>]
</li>
<li class="O">[<b>C83</b>] <a href="https://arxiv.org/abs/2312.06867">Get an A in Math: Progressive Rectification Prompting</a>
by Z. Wu, <b>M. Jiang</b>, C. Shen.
<i>AAAI Conference on Artificial Intelligence (<b>AAAI</b>)</i>, 2024.
[<a href="https://doi.org/10.1609/aaai.v38i17.29898">DOI</a>]
[<a href="https://wzy6642.github.io/prp.github.io/">project</a>]
</li>
<b>2023</b>
<li class="O">[<b>C82</b>] <a href="https://arxiv.org/abs/2305.14457">Pre-training Language Models for Comparative Reasoning</a>
by M. Yu, Z. Zhang, W. Yu, <b>M. Jiang</b>.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2023.
[<a href="https://doi.org/10.18653/v1/2023.emnlp-main.763">DOI</a>]
</li>
<li class="O">[<b>C81</b>] <a href="https://arxiv.org/abs/2305.14010">IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions</a>
by W. Yu, <b>M. Jiang</b>, P. Clark, A. Sabharwal.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2023.
[<a href="https://doi.org/10.18653/v1/2023.emnlp-main.515">DOI</a>]
</li>
<li class="O">[<b>C80</b>] <a href="https://arxiv.org/abs/2310.13127">Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models</a>
by Z. Zhang, S. Wang, W. Yu, Y. Xu, D. Iter, Q. Zeng, Y. Liu, C. Zhu, <b>M. Jiang</b>.
Findings of <i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2023.
[<a href="https://doi.org/10.18653/v1/2023.findings-emnlp.659">DOI</a>]
</li>
<li class="O">[<b>C79</b>] <a href="https://arxiv.org/abs/2303.10108">Data-Centric Learning from Unlabeled Graphs with Diffusion Model</a>
by G. Liu, E. Inae, T. Zhao, J. Xu, T. Luo, <b>M. Jiang</b>.
<i>Conference on Neural Information Processing Systems (<b>NeurIPS</b>)</i>, 2023.
</li>
<li class="O">[<b>C78</b>] <a href="https://arxiv.org/abs/2305.12087">Semi-Supervised Graph Imbalanced Regression</a>
by G. Liu, T. Zhao, E. Inae, T. Luo, <b>M. Jiang</b>.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2023.
[<a href="https://doi.org/10.1145/3580305.3599497">DOI</a>]
</li>
<li class="O">[<b>C77</b>] <a href="https://arxiv.org/abs/2305.09612">Large Language Models are Built-in Autoregressive Search Engines</a>
by N. Ziems, W. Yu, Z. Zhang, <b>M. Jiang</b>.
Findings of <i>Annual Meeting of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2023.
[<a href="https://doi.org/10.18653/v1/2023.findings-acl.167">DOI</a>]
</li>
<li class="O">[<b>C76</b>] <a href="https://ieeexplore.ieee.org/document/10225905">Explaining AI-informed Network Intrusion Detection with Counterfactuals</a>
by G. Liu, <b>M. Jiang</b>.
<i>IEEE International Conference on Computer Communications (<b>INFOCOM</b>)</i>, 2023.
[<a href="https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225905">DOI</a>]
</li>
<li class="O">[<b>C75</b>] <a href="https://arxiv.org/abs/2209.10063">Generate rather than Retrieve: Large Language Models are Strong Context Generators</a>
by W. Yu, D. Iter, S. Wang, Y. Xu, M. Ju, S. Sanyal, C. Zhu, M. Zeng, <b>M. Jiang</b>.
<i>International Conference on Learning Representations (<b>ICLR</b>)</i>, 2023.
</li>
<li class="O">[<b>C74</b>] <a href="https://arxiv.org/abs/2204.03508">A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods</a>
by Z. Zhang, W. Yu, M. Yu, Z. Guo, <b>M. Jiang</b>.
<i>Conference of the European Chapter of the Association for Computational Linguistics (<b>EACL</b>)</i>, 2023.
[<a href="https://doi.org/10.18653/v1/2023.eacl-main.66">DOI</a>]
</li>
<b>2022</b>
<li class="O">[<b>C73</b>] <a href="https://proceedings.mlr.press/v198/zhao22a.html">AutoGDA: Automated Graph Data Augmentation for Node Classification</a>
by T. Zhao, X. Tang, D. Zhang, H. Jiang, N. Rao, Y. Song, P. Agrawal, K. Subbian, B. Yin, <b>M. Jiang</b>.
<i>Learning on Graphs Conference (<b>LoG</b>)</i>, 2022.
</li>
<li class="O">[<b>C72</b>] <a href="https://aclanthology.org/2022.emnlp-main.43/">A Unified Encoder-Decoder Framework with Entity Memory</a>
by Z. Zhang, W. Yu, C. Zhu, <b>M. Jiang</b>.
<i>Empirical Methods on Natural Language Processing (<b>EMNLP</b>)</i>, 2022.
[<a href="https://doi.org/10.18653/v1/2022.emnlp-main.43">DOI</a>]
</li>
<li class="O">[<b>C71</b>] <a href="https://aclanthology.org/2022.emnlp-main.294/">Retrieval Augmentation for Commonsense Reasoning: A Unified Approach</a>
by W. Yu, C. Zhu, Z. Zhang, S. Wang, Z. Zhang, Y. Fang, <b>M. Jiang</b>.
<i>Empirical Methods on Natural Language Processing (<b>EMNLP</b>)</i>, 2022.
[<a href="https://doi.org/10.18653/v1/2022.emnlp-main.294">DOI</a>]
</li>
<li class="O">[<b>C70</b>] <a href="https://dl.acm.org/doi/abs/10.1145/3534678.3539347">Graph Rationalization with Environment-based Augmentations</a>
by G. Liu, T. Zhao, J. Xu, T. Luo, <b>M. Jiang</b>.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2022.
[<a href="https://doi.org/10.1145/3534678.3539347">DOI</a>]
</li>
<li class="O">[<b>C69</b>] <a href="https://dl.acm.org/doi/10.1145/3534678.3539171">Automatic Controllable Product Copywriting for E-Commerce</a>
by X. Guo, Q. Zeng, <b>M. Jiang</b>, X. Yun, B. Long, L. Wu.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2022.
[<a href="https://doi.org/10.1145/3534678.3539171">DOI</a>]
</li>
<li class="O">[<b>C68</b>] <a href="https://proceedings.mlr.press/v162/zhao22e/zhao22e.pdf">Learning from Counterfactual Links for Link Prediction</a>
by T. Zhao, G. Liu, D. Wang, W. Yu, <b>M. Jiang</b>.
<i>International Conference on Machine Learning (<b>ICML</b>)</i>, 2022.
[<a href="https://icml.cc/media/icml-2022/Slides/16774.pdf">slides</a>]
</li>
<li class="O">[<b>C67</b>] <a href="https://ieeexplore.ieee.org/abstract/document/9912074">Hardware/Software Co-Exploration for Graph Neural Architectures on FPGAs</a>
by Q. Lu, W. Jiang, <b>M. Jiang</b>, J. Hu, Y. Shi.
<i>IEEE Computer Society Annual Symposium on VLSI (<b>ISVLSI</b>)</i>, 2022.
[<a href="https://doi.org/10.1109/ISVLSI54635.2022.00079">DOI</a>]
</li>
<li class="O">[<b>C66</b>] <a href="https://dl.acm.org/doi/10.1145/3533406.3533418">A Bottom-Up End-User Intelligent Assistant Approach to Empower Gig Workers against AI Inequality</a>
by T. Li, Y. Lu, J. Clark, M. Chen, V. Cox, <b>M. Jiang</b>, Y. Yang, T. Kay, D. Wood, J. Brockman.
<i>Symposium on Human-Computer Interaction for Work (<b>CHIWORK</b>)</i>, 2022.
[<a href="https://doi.org/10.1145/3533406.3533418">DOI</a>]
</li>
<li class="O">[<b>C65</b>] <a href="https://aclanthology.org/2022.findings-acl.149/">Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts</a>
by W. Yu, C. Zhu, L. Qin, T. Zhao, <b>M. Jiang</b>.
Findings of <i>Annual Meeting of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2022.
[<a href="https://doi.org/10.18653/v1/2022.dlg4nlp-1.1">DOI</a>]
</li>
<li class="O">[<b>C64</b>] <a href="https://aclanthology.org/2022.findings-acl.150/">Dict-BERT: Enhancing Language Model Pre-training with Dictionary</a>
by W. Yu, C. Zhu, Y. Fang, D. Yu, S. Wang, Y. Xu, M. Zeng, <b>M. Jiang</b>.
Findings of <i>Annual Meeting of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2022.
[<a href="https://doi.org/10.18653/v1/2022.findings-acl.150">DOI</a>]
</li>
<b>2021</b>
<li class="O">[<b>C63</b>] <a href="https://arxiv.org/abs/2108.02074">Multi-Round Parsing-based Multiword Rules for Scientific OpenIE</a>
by J. Kuebler, L. Tong, <b>M. Jiang</b>.
<i>International Conference on Big Knowledge (<b>ICBK</b>)</i>, 2021.
</li>
<li class="O">[<b>C62</b>] <a href="https://ieeexplore.ieee.org/abstract/document/9679001">Dynamic Attributed Graph Prediction with Conditional Normalizing Flows</a>
by D. Wang, T. Zhao, N.V. Chawla, <b>M. Jiang</b>.
<i>International Conference on Data Mining (<b>ICDM</b>)</i>, 2021.
[<a href="https://doi.org/10.1109/ICDM51629.2021.00176">DOI</a>]
</li>
<li class="O">[<b>C61</b>] <a href="https://aclanthology.org/2021.emnlp-main.412/">Sentence-Permuted Paragraph Generation</a>
by W. Yu, C. Zhu, T. Zhao, Z. Guo, <b>M. Jiang</b>.
<i>Empirical Methods on Natural Language Processing (<b>EMNLP</b>)</i>, 2021.
[<a href="https://doi.org/10.18653/v1/2021.emnlp-main.412">DOI</a>]
</li>
<li class="O">[<b>C60</b>] <a href="https://aclanthology.org/2021.emnlp-main.56/">Injecting Entity Types into Entity-Guided News Generation</a>
by X. Dong*, W. Yu*, C. Zhu, <b>M. Jiang</b>.
<i>Empirical Methods on Natural Language Processing (<b>EMNLP</b>)</i>, 2021.
[<a href="https://doi.org/10.18653/v1/2021.emnlp-main.56">DOI</a>]
</li>
<li class="O">[<b>C59</b>] <a href="https://dl.acm.org/doi/10.1145/3459637.3482313">Action Sequence Augmentation for Early Graph-based Anomaly Detection</a>
by T. Zhao, B. Ni, W. Yu, Z. Guo, N. Shah, <b>M. Jiang</b>.
<i>ACM International Conference on Information and Knowledge Management (<b>CIKM</b>)</i>, 2021.
[<a href="https://doi.org/10.1145/3459637.3482313">DOI</a>]
</li>
<li class="O">[<b>C58</b>] <a href="https://dl.acm.org/doi/10.1145/3447548.3467308">Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations</a>
by Q. Zeng, J. Lin, W. Yu, J. Cleland-Huang, <b>M. Jiang</b>.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2021.
[<a href="https://doi.org/10.1145/3447548.3467308">DOI</a>]
</li>
<li class="O">[<b>C57</b>] <a href="https://dl.acm.org/doi/10.1145/3447548.3467282">Cross-Network Learning with Partially Aligned Graph Convolutional Networks</a>
by <b>M. Jiang</b>.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2021.
[<a href="https://doi.org/10.1145/3447548.3467282">DOI</a>]
</li>
<li class="O">[<b>C56</b>] <a href="https://aclanthology.org/2021.naacl-industry.23/">Technical Question Answering across Tasks and Domains</a>
by W. Yu, L. Wu, Q. Zeng, Y. Deng, R. Mahindru, S. Guven, <b>M. Jiang</b>.
<i>Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (<b>NAACL-HTL</b>)</i>, 2021.
[<a href="https://doi.org/10.18653/v1/2021.naacl-industry.23">DOI</a>]
</li>
<li class="O">[<b>C55</b>] <a href="https://aclanthology.org/2021.naacl-main.58/">Enhancing Factual Consistency of Abstractive Summarization</a>
by C. Zhu, W. Hinthorn, R. Xu, Q. Zeng, M. Zeng, X. Huang, <b>M. Jiang</b>.
<i>Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (<b>NAACL-HLT</b>)</i>, 2021.
[<a href="https://doi.org/10.18653/v1/2021.naacl-main.58">DOI</a>]
</li>
<li class="O">[<b>C54</b>] <a href="https://dl.acm.org/doi/10.1145/3442381.3450090">TCN: Table Convolutional Network for Web Table Interpretation</a>
by D. Wang, P. Shiralkar, C. Lockard, B. Huang, X.L. Dong, <b>M. Jiang</b>.
<i>The Web Conference (<b>TheWebConf</b>)</i>, 2021.
[<a href="https://doi.org/10.1145/3442381.3450090">DOI</a>]
</li>
<li class="O">[<b>C53</b>] <a href="https://dl.acm.org/doi/10.1145/3442381.3450112">Few-Shot Graph Learning for Molecular Property Prediction</a>
by Z. Guo, C. Zhang, W. Yu, J. Herr, O. Wiest, <b>M. Jiang</b>, N.V. Chawla.
<i>The Web Conference (<b>TheWebConf</b>)</i>, 2021.
[<a href="https://doi.org/10.1145/3442381.3450112">DOI</a>]
</li>
<li class="O">[<b>C52</b>] <a href="https://ieeexplore.ieee.org/document/9402118">Traceability Transformed: Generating More Accurate Links with Pre-Trained BERT Models</a>
by J. Lin, Y. Liu, Q. Zeng, <b>M. Jiang</b>, J. Huang.
<i>International Conference on Software Engineering (<b>ICSE</b>)</i>, 2021. (<b style="color:red">ACM SIGSOFT Distinguished Paper Award</b>)
[<a href="https://doi.org/10.1109/ICSE43902.2021.00040">DOI</a>]
</li>
<li class="O">[<b>C51</b>] <a href="https://ojs.aaai.org/index.php/AAAI/article/view/17315">Data Augmentation for Graph Neural Networks</a>
by T. Zhao, Y. Liu, L. Neves, O. Woodford, <b>M. Jiang</b>, N. Shah.
<i>AAAI Conference on Artificial Intelligence (<b>AAAI</b>)</i>, 2021.
[<a href="https://doi.org/10.1609/aaai.v35i12.17315">DOI</a>]
</li>
<b>2020</b>
<li class="O">[<b>C50</b>] <a href="https://ieeexplore.ieee.org/document/9313188">Imputing Growth Snapshot Similarity in Early Childhood Development: A Tensor Decomposition Approach</a>
by J. Schnur, R. Karl, A. Garcia-Martinez, <b>M. Jiang</b>, N.V. Chawla.
<i>IEEE International Conference on Bioinformatics and Biomedicine (<b>BIBM</b>)</i>, 2020.
[<a href="https://doi.org/10.1109/BIBM49941.2020.9313188">DOI</a>]
</li>
<li class="O">[<b>C49</b>] <a href="https://ieeexplore.ieee.org/document/9313110">Use of Internal Knowledge: Biomedical Literature Search Liberated From External Resources</a>
by T. Jiang, N. Zhang, M. Liu, <b>M. Jiang</b>, T. Liu, B. Qin.
<i>IEEE International Conference on Bioinformatics and Biomedicine (<b>BIBM</b>)</i>, 2020.
[<a href="https://doi.org/10.1109/BIBM49941.2020.9313110">DOI</a>]
</li>
<li class="O">[<b>C48</b>] <a href="https://ieeexplore.ieee.org/document/9381444">Overcoming Data Sparsity in Predicting User Characteristics from Behavior through Graph Embeddings</a>
by M. Syed, D. Wang, <b>M. Jiang</b>, O. Conway, V. Juneja, S. Subramanian, N.V. Chawla.
<i>IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (<b>ASONAM</b>)</i>, 2020.
[<a href="https://doi.org/10.1109/ASONAM49781.2020.9381444">DOI</a>]
</li>
<li class="O">[<b>C47</b>] <a href="https://aclanthology.org/2020.emnlp-demos.13/">A Technical Question Answering System with Transfer Learning</a>
by W. Yu, L. Wu, Y. Deng, R. Mahindru, Q. Zeng, S. Guven, <b>M. Jiang</b>.
<i>Findings of Empirical Methods on Natural Language Processing (<b>EMNLP</b>)</i>, 2020.
[<a href="https://doi.org/10.18653/v1/2020.emnlp-demos.13">DOI</a>]
</li>
<li class="O">[<b>C46</b>] <a href="https://aclanthology.org/2020.findings-emnlp.429/">Tri-Train: Automatic Pre-fine Tuning between Pre-training and Fine-tune Training for SciNER</a>
by Q. Zeng, W. Yu, M. Yu, T. Jiang, T. Weninger, <b>M. Jiang</b>.
<i>Findings of Empirical Methods on Natural Language Processing (<b>EMNLP</b>)</i>, 2020.
[<a href="https://doi.org/10.18653/v1/2020.findings-emnlp.429">DOI</a>]
</li>
<li class="O">[<b>C45</b>] <a href="https://aclanthology.org/2020.findings-emnlp.51/">Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases</a>
by C. Zhang, L. Yu, M. Saebi, <b>M. Jiang</b>, N. Chawla.
<i>Findings of Empirical Methods on Natural Language Processing (<b>EMNLP</b>)</i>, 2020.
[<a href="https://doi.org/10.18653/v1/2020.findings-emnlp.51">DOI</a>]
</li>
<li class="O">[<b>C44</b>] <a href="https://dl.acm.org/doi/10.1145/3340531.3411981">GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction</a>
by Z. Guo, W. Yu, C. Zhang, <b>M. Jiang</b>, N. Chawla.
<i>ACM International Conference on Information and Knowledge Management (<b>CIKM</b>)</i>, 2020.
[<a href="https://doi.org/10.1145/3340531.3411981">DOI</a>]
</li>
<li class="O">[<b>C43</b>] <a href="https://dl.acm.org/doi/10.1145/3340531.3411979">Error-bounded Graph Anomaly Loss for GNNs</a>
by T. Zhao, C. Deng, K. Yu, T. Jiang, D. Wang, <b>M. Jiang</b>.
<i>ACM International Conference on Information and Knowledge Management (<b>CIKM</b>)</i>, 2020.
[<a href="https://doi.org/10.1145/3340531.3411979">DOI</a>]
</li>
<li class="O">[<b>C42</b>] <a href="https://ieeexplore.ieee.org/document/9218137">Towards Semantically Guided Traceability</a>
by Y. Liu, J. Lin, Q. Zeng, <b>M. Jiang</b>, J. Cleland-Huang.
<i>IEEE International Requirements Engineering Conference (<b>RE</b>)</i>, 2020.
[<a href="https://doi.org/10.1109/RE48521.2020.00043">DOI</a>]
</li>
<li class="O">[<b>C41</b>] <a href="https://dl.acm.org/doi/10.1145/3394486.3403308">Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors</a>
by D. Wang, <b>M. Jiang</b>, M. Syed, O. Conway, V. Juneja, S. Subramanian, N. Chawla.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2020.
[<a href="https://doi.org/10.1145/3394486.3403308">DOI</a>]
</li>
<li class="O">[<b>C40</b>] <a href="https://aclanthology.org/2020.acl-main.498/">Crossing Variational Autoencoders for Answer Retrieval</a>
by W. Yu, L. Wu, Q. Zeng, S. Tao, Y. Deng, <b>M. Jiang</b>.
<i>Annual Meeting of the Association for Computational Linguistics (<b>ACL</b>)</i>, 2020.
[<a href="https://doi.org/10.18653/v1/2020.acl-main.498">DOI</a>]
</li>
<li class="O">[<b>C39</b>] <a href="https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11413/2556746/Improving-situational-awareness-with-collective-artificial-intelligence-over-knowledge-graphs/10.1117/12.2556746.short">Improving Situational Awareness with Collective Artificial Intelligence over Knowledge Graphs</a>
by <b>M. Jiang</b>.
<i>Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II in SPIE Defense + Commercial Sensing Symposium</i>, 2020.
[<a href="https://doi.org/10.1117/12.2556746">DOI</a>]
</li>
<li class="O">[<b>C38</b>] <a href="https://dl.acm.org/doi/10.1145/3366423.3380175">Identifying Referential Intention with Heterogeneous Contexts</a>
by W. Yu, M. Yu, T. Zhao, <b>M. Jiang</b>.
<i>The Web Conference (<b>TheWebConf</b>)</i>, 2020.
[<a href="https://doi.org/10.1145/3366423.3380175">DOI</a>]
</li>
<li class="O">[<b>C37</b>] <a href="https://dl.acm.org/doi/10.1145/3366423.3380174">Experimental Evidence Extraction in Data Science with Hybrid Table Features and Ensemble Learning</a>
by W. Yu, W. Peng, Y. Shu, Q. Zeng, <b>M. Jiang</b>.
<i>The Web Conference (<b>TheWebConf</b>)</i>, 2020.
[<a href="https://doi.org/10.1145/3366423.3380174">DOI</a>]
</li>
<li class="O">[<b>C36</b>] <a href="https://ojs.aaai.org/index.php/AAAI/article/view/6435">Multi-label Patent Categorization with Non-local Attention-based Graph Convolutional Network</a>
by P. Tang, <b>M. Jiang</b>, N. Xia, J. Pitera, J. Welser, N. Chawla.
<i>AAAI Conference on Artificial Intelligence (<b>AAAI</b>)</i>, 2020.
[<a href="https://doi.org/10.1609/aaai.v34i05.6435">DOI</a>]
</li>
<li class="O">[<b>C35</b>] <a href="https://ojs.aaai.org/index.php/AAAI/article/view/5698">Few-Shot Knowledge Graph Completion</a>
by C. Zhang, H. Yao, <b>M. Jiang</b>, Z. Li, N. Chawla.
<i>AAAI Conference on Artificial Intelligence (<b>AAAI</b>)</i>, 2020.
[<a href="https://doi.org/10.1609/aaai.v34i03.5698">DOI</a>]
</li>
<li class="O">[<b>C34</b>] <a href="https://ojs.aaai.org/index.php/AAAI/article/view/6142">Graph Few-shot Learning via Knowledge Transfer</a>
by H. Yao, C. Zhang, Y. Wei, <b>M. Jiang</b>, S. Wang, N. Chawla, Z. Li.
<i>AAAI Conference on Artificial Intelligence (<b>AAAI</b>)</i>, 2020.
[<a href="https://doi.org/10.1609/aaai.v34i04.6142">DOI</a>]
</li>
<b>2019</b>
<li class="O">[<b>C33</b>] <a href="https://ieeexplore.ieee.org/document/9006493">Preserving Composition and Crystal Structure Information of Chemical Compounds in Atomic Embedding</a>
by Y. Ding, D. Wang, T. Weninger, <b>M. Jiang</b>.
<i>IEEE International Conference on Big Data (<b>BigData</b>)</i>, 2019.
[<a href="https://doi.org/10.1109/BigData47090.2019.9006493">DOI</a>]
</li>
<li class="O">[<b>C32</b>] <a href="https://ieeexplore.ieee.org/document/8983173">CTGA: Graph-based Biomedical Literature Search</a>
by T. Jiang, Z. Zhang, T. Zhao, B. Qin, T. Liu, N. Chawla, <b>M. Jiang</b>.
<i>IEEE International Conference on Bioinformatics and Biomedicine (<b>BIBM</b>)</i>, 2019.
[<a href="https://doi.org/10.1109/BIBM47256.2019.8983173">DOI</a>]
</li>
<li class="O">[<b>C31</b>] <a href="https://aclanthology.org/D19-1029/">Multi-input Multi-output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text</a>
by T. Jiang, T. Zhao, B. Qin, T. Liu, N. Chawla, <b>M. Jiang</b>.
<i>Conference on Empirical Methods in Natural Language Processing (<b>EMNLP</b>)</i>, 2019.
[<a href="https://doi.org/10.18653/v1/D19-1029">DOI</a>]
</li>
<li class="O">[<b>C30</b>] <a href="https://link.springer.com/chapter/10.1007/978-3-030-32245-8_68">MSU-Net: Multiscale Statistical U-Net forReal-time 3D Cardiac MRI Video Segmentation</a>
by T. Wang, X. Xu, J. Xiong, <b>M. Jiang</b>, Y. Shi.
<i>International Conference on Medical Image Computing and Computer Assisted Intervention (<b>MICCAI</b>)</i>, 2019.
[<a href="https://doi.org/10.1007/978-3-030-32245-8_68">DOI</a>]
</li>
<li class="O">[<b>C29</b>] <a href="https://dl.acm.org/doi/10.1145/3292500.3330942">The Role of 'Condition': A Novel Scientific Knowledge Graph Representation and Construction Model</a>
by T. Jiang, T. Zhao, B. Qin, T. Liu, N. Chawla, <b>M. Jiang</b>.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2019.
[<a href="https://doi.org/10.1145/3292500.3330942">DOI</a>]
</li>
<li class="O">[<b>C28</b>] <a href="https://dl.acm.org/doi/10.1145/3292500.3330867">TUBE: Embedding Behavior Outcomes for Predicting Success</a>
by D. Wang, T. Jiang, N. Chawla, <b>M. Jiang</b>.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2019.
[<a href="https://doi.org/10.1145/3292500.3330867">DOI</a>]
</li>
<li class="O">[<b>C27</b>] <a href="https://dl.acm.org/doi/10.1145/3308558.3314118">Tablepedia: Automating PDF Table Reading in an Experimental Evidence Exploration and Analytic System</a>
by W. Yu, Z. Li, Q. Zeng, <b>M. Jiang</b>.
<i>The Web Conference (<b>TheWebConf</b>)</i>, 2019.
[<a href="https://doi.org/10.1145/3308558.3314118">DOI</a>]
</li>
<li class="O">[<b>C26</b>] <a href="https://dl.acm.org/doi/10.1145/3308558.3313435">A Novel Unsupervised Approach for Precise Temporal Slot Filling from Incomplete and Noisy Temporal Contexts</a>
by X. Wang, H. Zhang, Q. Li, Y. Shi, <b>M. Jiang</b>.
<i>The Web Conference (<b>TheWebConf</b>)</i>, 2019.
[<a href="https://doi.org/10.1145/3308558.3313435">DOI</a>]
</li>
<b>2018</b>
<li class="O">[<b>C25</b>] <a href="https://ieeexplore.ieee.org/document/8621975">Actionable Objective Optimization for Suspicious Behavior Detection on Large Bipartite Graphs</a>
by T. Zhao, M. Malir, <b>M. Jiang</b>.
<i>IEEE International Conference on Big Data (<b>BigData</b>)</i>, 2018.
[<a href="https://doi.org/10.1109/BigData.2018.8621975">DOI</a>]
</li>
<li class="O">[<b>C24</b>] <a href="https://ieeexplore.ieee.org/document/8594978">Doc2Cube: Allocating Documents to Text Cube without Labeled Data</a>
by F. Tao, C. Zhang, X. Chen, <b>M. Jiang</b>, T. Hanratty, L. Kaplan, J. Han.
<i>IEEE International Conference on Data Mining (<b>ICDM</b>)</i>, 2018.
[<a href="https://doi.org/10.1109/ICDM.2018.00169">DOI</a>]
</li>
<li class="O">[<b>C23</b>] <a href="https://dl.acm.org/doi/10.1145/3269206.3272024">Optimizing Boiler Control in Real-Time with Machine Learning for Sustainability</a>
by Y. Ding, J. Liu, J. Xiong, <b>M. Jiang</b>, Y. Shi.
<i>ACM International Conference on Information and Knowledge Management (<b>CIKM</b>)</i>, 2018.
[<a href="https://doi.org/10.1145/3269206.3272024">DOI</a>]
</li>
<li class="O">[<b>C22</b>] <a href="https://dl.acm.org/doi/10.1145/3233547.3233555">CausalTriad: Toward Pseudo Causal Relation Discovery and Hypotheses Generation from Medical Text Data</a>
by S. Zhao, <b>M. Jiang</b>, M. Liu, B. Qin, T. Liu.
<i>ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (<b>BCB</b>)</i>, 2018.
[<a href="https://doi.org/10.1145/3233547.3233555">DOI</a>]
</li>
<li class="O">[<b>C21</b>] <a href="https://dl.acm.org/doi/10.1145/3219819.3219949">A Project Showcase for Planning Research Work towards Publishable Success</a>
by D. Wang, <b>M. Jiang</b>, X. Wang, T. Zhao, Q. Zeng, N.V. Chawla.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2018.
[<a href="https://doi.org/10.1145/3219819.3219949">DOI</a>]
</li>
<li class="O">[<b>C20</b>] <a href="https://dl.acm.org/doi/10.1145/3219819.3220064">TaxoGen: Constructing Topical Concept Taxonomy by Adaptive Term Embedding and Clustering</a>
by C. Zhang, F. Tao, X. Chen, J. Shen, <b>M. Jiang</b>, B. Sadler, M. Vanni, J. Han.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2018.
[<a href="https://doi.org/10.1145/3219819.3220064">DOI</a>]
</li>
<li class="O">[<b>C19</b>] <a href="https://dl.acm.org/doi/10.1145/3219819.3220017">TruePIE: Discovering Reliable Patterns in Pattern-Based Information Extraction</a>
by <b>M. Jiang</b>*, Q. Li*, X. Zhang, M. Qu, T. Hanratty, J. Gao, J. Han.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2018. (* for equal contribution)
[<a href="https://doi.org/10.1145/3219819.3220017">DOI</a>]
</li>
<li class="O">[<b>C18</b>] <a href="https://dl.acm.org/doi/10.1145/3219819.3219949">Multi-Type Itemset Embedding for Learning Behavior Success</a>
by D. Wang, <b>M. Jiang</b>, Q. Zeng, Z. Eberhart, N.V. Chawla.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2018.
[<a href="https://doi.org/10.1145/3219819.3219949">DOI</a>]
</li>
<b>2017</b>
<li class="O">[<b>C17</b>] <a href="https://aclanthology.org/P17-4010/">LifeNet: A Structured Network-Based Knowledge Exploration and Analytics System for Life Sciences</a>
by X. Ren, J. Shen, M. Qu, X. Wang, Z. Wu, Q. Zhu, <b>M. Jiang</b>, F. Tao, S. Sinha, D. Liem, P. Ping, R. Weinshilboum, J. Han. Annual Meeting of the Association for Computational Linguistics (<b>ACL</b>), 2017.
</li>
<li class="O">[<b>C16</b>] <a href="https://dl.acm.org/doi/10.1145/3097983.3098105">MetaPAD: Meta Patten Discovery from Massive Text Corpora</a>
by <b>M. Jiang</b>, J. Shang, T. Cassidy, X. Ren, L. Kaplan, T. Hanratty, J. Han.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2017.
[<a href="https://doi.org/10.1145/3097983.3098105">DOI</a>]
</li>
<li class="O">[<b>C15</b>] <a href="https://dl.acm.org/doi/10.1145/3097983.3098032">Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing</a>
by K. Kuang, P. Cui, B. Li, <b>M. Jiang</b>, S. Yang.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2017.
[<a href="https://doi.org/10.1145/3097983.3098032">DOI</a>]
</li>
<li class="O">[<b>C14</b>] <a href="https://www.ijcai.org/proceedings/2017/489">ContextCare: Incorporating Contextual Information Networks to Representation Learning in Medical Forum Data</a>
by S. Zhao, <b>M. Jiang</b>, Q. Yuan, B. Qin, T. Liu, C.X. Zhai.
<i>International Joint Conference on Artificial Intelligence (<b>IJCAI</b>)</i>, 2017.
[<a href="https://doi.org/10.24963/ijcai.2017/489">DOI</a>]
</li>
<li class="O">[<b>C13</b>] <a href="https://dl.acm.org/doi/10.5555/3298239.3298261">Treatment Effect Estimation with Data-Driven Variable Decomposition</a>
by K. Kuang, P. Cui, B. Li, <b>M. Jiang</b>, S. Yang, F. Wang.
<i>AAAI Conference on Artificial Intelligence (<b>AAAI</b>)</i>, 2017.
</li>
<b>2016</b>
<li class="O">[<b>C12</b>] <a href="https://ieeexplore.ieee.org/document/7837937">Steering Social Media Promotions with Effective Strategies</a>
by K. Kuang, <b>M. Jiang</b>, P. Cui, S. Yang.
<i>IEEE International Conference on Data Mining (<b>ICDM</b>)</i>, 2016.
[<a href="https://doi.org/10.1109/ICDM.2016.0124">DOI</a>]
</li>
<li class="O">[<b>C11</b>] <a href="https://ieeexplore.ieee.org/document/7837924">Large-Scale Embedding Learning in Heterogeneous Event Data</a>
by H. Gui, J. Liu, F. Tao, <b>M. Jiang</b>, B. Norick, J. Han.
<i>IEEE International Conference on Data Mining (<b>ICDM</b>)</i>, 2016.
[<a href="https://doi.org/10.1109/ICDM.2016.0111">DOI</a>]
</li>
<li class="O">[<b>C10</b>] <a href="https://dl.acm.org/doi/10.1145/2939672.2939749">CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors</a>
by <b>M. Jiang</b>, C. Faloutsos, J. Han.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2016.
[<a href="https://doi.org/10.1145/2939672.2939749">DOI</a>]
</li>
<li class="O">[<b>C9</b>] <a href="https://ojs.aaai.org/index.php/AAAI/article/view/10001">Little is Much: Bridging Cross-Platform Behaviors through Overlapped Crowds</a>
by <b>M. Jiang</b>, P. Cui, N. J. Yuan, X. Xie, S. Yang.
<i>AAAI Conference on Artificial Intelligence (<b>AAAI</b>)</i>, 2016.
[<a href="https://doi.org/10.1609/aaai.v30i1.10001">DOI</a>]
</li>
<b>2010-2015</b>
<li class="O">[<b>C8</b>] <a href="https://ieeexplore.ieee.org/document/7373389">A General Suspiciousness Metric for Dense Blocks in Multimodal Data</a>
by <b>M. Jiang</b>, A. Beutel, P. Cui, B. Hooi, S. Yang, C. Faloutsos.
<i>IEEE International Conference on Data Mining (<b>ICDM</b>)</i>, 2015.
[<a href="https://doi.org/10.1109/ICDM.2015.61">DOI</a>]
</li>
<li class="O">[<b>C7</b>] <a href="https://dl.acm.org/doi/10.1145/2623330.2623644">FEMA: Flexible Evolutionary Multi-Faceted Analysis for Dynamic Behavioral Pattern Discovery</a>
by <b>M. Jiang</b>, P. Cui, F. Wang, X. Xu, W. Zhu, S. Yang.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2014.
[<a href="https://doi.org/10.1145/2623330.2623644">DOI</a>]
</li>
<li class="O">[<b>C6</b>] <a href="https://dl.acm.org/doi/10.1145/2623330.2623632">CatchSync: Catching Synchronized Behavior in Large Directed Graphs</a>
by <b>M. Jiang</b>, P. Cui, A. Beutel, C. Faloutsos, S. Yang.
<i>ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (<b>KDD</b>)</i>, 2014.
(<b style="color:red">Best Paper Finalist</b>)
[<a href="https://doi.org/10.1145/2623330.2623632">DOI</a>]
</li>
<li class="O">[<b>C5</b>] <a href="https://link.springer.com/chapter/10.1007/978-3-319-06608-0_11">Inferring Strange Behavior from Connectivity Pattern in Social Networks</a>
by <b>M. Jiang</b>, P. Cui, A. Beutel, C. Faloutsos, S. Yang.
<i>Pacific-Asia Conference on Knowledge Discovery and Data Mining (<b>PAKDD</b>)</i>, 2014.
[<a href="https://doi.org/10.1007/978-3-319-06608-0_11">DOI</a>]
</li>
<li class="O">[<b>C4</b>] <a href="https://dl.acm.org/doi/10.1145/2567948.2577306">Detecting Suspicious Following Behavior in Multimillion-Node Social Networks</a>
by <b>M. Jiang</b>, P. Cui, A. Beutel, C. Faloutsos, S. Yang.
<i>International Conference on World Wide Web (<b>WWW</b>)</i>, 2014.
[<a href="https://doi.org/10.1145/2567948.2577306">DOI</a>]
</li>
<li class="O">[<b>C3</b>] <a href="https://dl.acm.org/doi/10.1145/2396761.2398448">Social Recommendation across Multiple Relational Domains</a>
by <b>M. Jiang</b>, P. Cui, F. Wang, Q. Yang, W. Zhu, S. Yang.
<i>ACM International Conference on Information and Knowledge Management (<b>CIKM</b>)</i>, 2012.
[<a href="https://doi.org/10.1145/2396761.2398448">DOI</a>]
</li>
<li class="O">[<b>C2</b>] <a href="https://dl.acm.org/doi/10.1145/2396761.2396771">Social Contextual Recommendation</a>
by <b>M. Jiang</b>, P. Cui, R. Liu, Q. Yang, F. Wang, W. Zhu, S. Yang.
<i>ACM International Conference on Information and Knowledge Management (<b>CIKM</b>)</i>, 2012.
[<a href="https://doi.org/10.1145/2396761.2396771">DOI</a>]
</li>
<li class="O">[<b>C1</b>] <a href="https://dl.acm.org/doi/10.1145/1871437.1871467">Mining Topic-Level Influence in Heterogeneous Networks</a>
by L. Liu, J. Tang, J. Han, <b>M. Jiang</b>, S. Yang.
<i>ACM International Conference on Information and Knowledge Management (<b>CIKM</b>)</i>, 2010.
[<a href="https://doi.org/10.1145/1871437.1871467">DOI</a>]
</li>
</ul>
<h2>Journal Papers</h2>
<ul>
<b>2026</b>
<li class="O">[<b>J49</b>] <a href="https://arxiv.org/abs/2509.11452">Learning to Optimize Multi-Objective Alignment Through Dynamic Reward Weighting</a>
by Y. Lu, Z. Wang, S. Li, X. Liu, C. Yu, Q. Yin, Z. Shi, Z. Zhang, <b>M. Jiang</b>.
<i>Transactions of the Association for Computational Linguistics (<b>TACL</b>)</i>, February 2026.
</li>
<b>2025</b>
<li class="O">[<b>J48</b>] <a href="#">Leveraging Historical Information to Boost Retrieval-Augmented Generation in Conversations</a>
by F. Mo, Y. Gao, Z. Wu, X. Liu, P. Chen, Z. Li, Z. Wang, X. Li, <b>M. Jiang</b>, J. Nie.
<i>Information Processing and Management</i>, October 2025.
</li>
<li class="O">[<b>J47</b>] <a href="https://link.springer.com/article/10.1557/s43577-025-00959-y">Computation and Machine Learning for Materials: Past, Present, and Future Perspectives</a>
by S. Alosious, <b>M. Jiang</b>, T. Luo.
<i>MRS Bulletin: 50th Anniversary</i>, September 2025.
</li>
<li class="O">[<b>J46</b>] <a href="https://www.dl.begellhouse.com/references/5756967540dd1b03,23402273003591c5,5705e9057954139b.html">Machine Learning in Nanoscale Thermal Transport</a>
by Y. Liu, S. Alosious, J. Zhou, <b>M. Jiang</b>, T. Luo.
<i>Annual Review of Heat Transfer</i>, June 2025.
</li>
<li class="O">[<b>J45</b>] <a href="https://arxiv.org/abs/2410.01744">Leopard: A Vision Language Model for Text-Rich Multi-Image Tasks</a>
by M. Jia, W. Yu, K. Ma, T. Fang, Z. Zhang, S. Ouyang, H. Zhang, D. Yu, <b>M. Jiang</b>.
<i>Transactions on Machine Learning Research (<b>TMLR</b>)</i>, May 2025.
</li>
<li class="O">[<b>J44</b>] <a href="#">Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices</a>
by R. Qin, D. Liu, C. Xu, Z. Yan, Z. Tan, Z. Jia, A. Nassereldine, J. Li, <b>M. Jiang</b>, A. Abbasi, J. Xiong, Y. Shi.
<i>ACM Transactions on Design Automation of Electronic Systems (<b>TODAES</b>)</i>, May 2025. (<b style="color:red">Selected as the Editor's Pick from Issue 5, 2025</b>)
</li>
<b>2024</b>
<li class="O">[<b>J43</b>] <a href="https://pubs.aip.org/aip/cpr/article-abstract/5/4/041311/3326540/Transcend-the-boundaries-Machine-learning-for">Transcend the Boundaries: Machine Learning for Designing Polymeric Membrane Materials for Gas Separation</a>
by J. Xu, A. Suleiman, G. Liu, R. Zhang, <b>M. Jiang</b>, R. Guo, T. Luo.
<i>Chemical Physics Reviews</i>, December 2024.
[<a href="https://doi.org/10.1063/5.0205433">DOI</a>]
</li>
<li class="O">[<b>J42</b>] <a href="https://arxiv.org/abs/2312.02783">Large Language Models on Graphs: A Comprehensive Survey</a>
by B. Jin, G. Liu, C. Han, <b>M. Jiang</b>, H. Ji, J. Han.
<i>IEEE Transactions on Knowledge and Data Engineering (<b>TKDE</b>)</i>, December 2024.
[<a href="https://doi.org/10.1109/TKDE.2024.3469578">DOI</a>]
</li>
<li class="O">[<b>J41</b>] <a href="https://academic.oup.com/bioinformaticsadvances/article/4/1/vbae099/7732851">Current and Future Directions in Network Biology</a>
by M. Zitnik, and many others including <b>M. Jiang</b>.
<i>Bioinformatics Advances</i>, August 2024.
[<a href="https://doi.org/10.1093/bioadv/vbae099">DOI</a>]
</li>
<li class="O">[<b>J40</b>] <a href="https://www.sciencedirect.com/science/article/pii/S2666386424003369">Superior Polymeric Gas Separation Membrane Designed by Explainable Graph Machine Learning</a>
by J. Xu, A. Suleiman, G. Liu, M. Perez, R. Zhang, <b>M. Jiang</b>, R. Guo, T. Luo.
<i>Cell Reports Physical Science</i>, June 2024.
[<a href="https://doi.org/10.1016/j.xcrp.2024.102067">DOI</a>]
</li>
<li class="O">[<b>J39</b>] <a href="https://onlinelibrary.wiley.com/doi/10.1002/admt.202301286">Autonomous Output-Oriented Aerosol Jet Printing Enabled by Hybrid Machine Learning</a>
by Y. Du, <b>M. Jiang</b>, Y. Zhang.
<i>Advanced Materials Technologies</i>, February 2024.
[<a href="https://dl.acm.org/doi/10.1002/admt.202301286">DOI</a>]
</li>
<li class="O">[<b>J38</b>] <a href="https://dl.acm.org/doi/10.1145/3638781">Rationalizing Graph Neural Networks with Data Augmentation</a>
by G. Liu, E. Inae, T. Luo, <b>M. Jiang</b>.
<i>ACM Transactions on Knowledge Discovery from Data (<b>TKDD</b>)</i>, February 2024.
[<a href="https://dl.acm.org/doi/10.1145/3638781">DOI</a>]
</li>
<b>2023</b>
<li class="O">[<b>J37</b>] <a href="https://arxiv.org/abs/2312.11518">User Modeling in the Era of Large Language Models</a>
by Z. Tan, <b>M. Jiang</b>.
<i>IEEE Data Engineering Bulletin</i>, December 2023.
</li>
<li class="O">[<b>J36</b>] <a href="https://ieeexplore.ieee.org/document/9758834">Deep Multimodal Complementarity Learning</a>
by D. Wang, T. Zhao, W. Yu, N.V. Chawla, <b>M. Jiang</b>.
<i>IEEE Transactions on Neural Networks and Learning Systems (<b>TNNLS</b>)</i>, December 2023.
[<a href="https://doi.org/10.1109/TNNLS.2022.3165180">DOI</a>]
</li>
<li class="O">[<b>J35</b>] <a href="https://dl.acm.org/doi/10.1145/3617376">Transfer Learning across Graph Convolutional Networks: Methods, Theory, and Applications</a>
by <b>M. Jiang</b>.
<i>ACM Transactions on Knowledge Discovery from Data (<b>TKDD</b>)</i>, October 2023.
[<a href="https://dl.acm.org/doi/10.1145/3617376">DOI</a>]
</li>
<li class="O">[<b>J34</b>] <a href="https://doi.org/10.1162/tacl_a_00591">Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions</a>
by Z. Zhang, W. Yu, Z. Ning, M. Ju, <b>M. Jiang</b>.
<i>Transactions of the Association for Computational Linguistics (<b>TACL</b>)</i>, August 2023.
[<a href="https://doi.org/10.1162/tacl_a_00591">DOI</a>]
</li>
<li class="O">[<b>J33</b>] <a href="http://sites.computer.org/debull/A23june/p138.pdf">Graph Data Augmentation for Graph Machine Learning: A Survey</a>
by T. Zhao, W. Jin, Y. Liu, Y. Wang, G. Liu, S. Gunnemann, N. Shah, <b>M. Jiang</b>.
<i>IEEE Data Engineering Bulletin</i>, June 2023.
[<a href="https://github.com/zhao-tong/graph-data-augmentation-papers">Readlist</a>]
</li>
<li class="O">[<b>J32</b>] <a href="https://ieeexplore.ieee.org/document/9472956">Modeling Co-evolution of Attributed and Structural Information in Graph Sequence</a>
by D. Wang, Z. Zhang, Y. Ma, T. Zhao, T. Jiang, N.V. Chawla, <b>M. Jiang</b>.
<i>IEEE Transactions on Knowledge and Data Engineering (<b>TKDE</b>)</i>, February 2023.
[<a href="https://doi.org/10.1109/TKDE.2021.3094332">DOI</a>]
</li>
<b>2022</b>
<li class="O">[<b>J31</b>] <a href="https://dl.acm.org/doi/abs/10.1145/3472753">A Survey on Data-Driven Network Intrusion Detection</a>
by D. Chou, <b>M. Jiang</b>.
<i>ACM Computing Surveys (<b>CSUR</b>)</i>, December 2022.
[<a href="https://doi.org/10.1145/3472753">DOI</a>]
</li>
<li class="O">[<b>J30</b>] <a href="https://www.sciencedirect.com/science/article/pii/S1566253522000604">Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning</a>
by M. Saebi, S. Kreig, C. Zhang, <b>M. Jiang</b>, T. Kajdanowicz, N.V. Chawla.