UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

up-to-date curated list of state-of-the-art Large vision language models hallucinations research work, papers & resources

[ICLR 2025] MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation

Always keep your codebases ready for Agents. Improve any coding workflow by atleast 2x by maintaing a live, pluggable context layer per repo that creates and maintains Agents.md

[ACL 2024] ANAH & [NeurIPS 2024] ANAH-v2 & [ICLR 2025] Mask-DPO

[EMNLP'25] A novel alignment framework that leverages image retrieval to mitigate hallucinations in Vision Language Models.

FastMemory is a topological representation of text data using concepts as the primary input. It helps in improving the RAG(by replacing embedding and vectors entirely), AI memory and LLM queries by upto 100% as in the huggingface benchmarks(22+ SOTA)

[ICLR 2025] Data-Augmented Phrase-Level Alignment for Mitigating Object Hallucination

✨ Official code for our paper: "Uncertainty-o: One Model-agnostic Framework for Unveiling Epistemic Uncertainty in Large Multimodal Models".

AEP (Agent Element Protocol) v2.5 | Deterministic zero-trust total control and governance protocol for AI agents. | Reduce hallucinations to zero through architecure in all constrained domains of application. | LLMs gave you the engines, AEP gives you the control for the thrusters.

Official implementation for the NeurIPS 2025 paper: "FlexAC: Towards Flexible Control of Associative Reasoning in Multimodal Large Language Models". A lightweight, training-free framework for modulating associative behavior in MLLMs.

Oscillink — Self‑Optimizing Coherent Memory for Embedding Workflows

Official PyTorch implementation of "LPOI: Listwise Preference Optimization for Vision Language Models" (ACL 2025 Main)

A collection of papers on LLM/LVLM hallucination evaluation, detection, and mitigation

[ACL 2026] 📷 CCD: Mitigating Hallucinations in Radiology MLLMs via Clinical Contrastive Decoding — A flexible, plug-and-play toolkit for various radiology MLLM backbones, further boosting overall performance

[NeurIPS 2025] Official implementation for ''Robust Hallucination Detection in LLMs via Adaptive Token Selection'' https://arxiv.org/abs/2504.07863

[CVPR 2025 Workshop] PAINT (Paying Attention to INformed Tokens) is a plug-and-play framework that intervenes in the self-attention of the LLM and selectively boost the visual attention informed tokens to mitigate hallucination of Vision Language Models

Stop hallucinations by verifying citations.

Unofficial implementation of Microsoft’s Claimify Paper: extracts specific, verifiable, decontextualized claims from LLM Q&A to be used for Hallucination, Groundedness, Relevancy and Truthfulness detection

Agentic-AI framework w/o the headaches