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#

hallucination-mitigation

Here are 17 public repositories matching this topic...

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

  • UpdatedApr 30, 2025
  • Python

A novel alignment framework that leverages image retrieval to mitigate hallucinations in Vision Language Models.

  • UpdatedApr 21, 2025
  • Python

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

  • UpdatedMar 13, 2025
  • Python

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

  • UpdatedJan 27, 2025
  • Python

[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

  • UpdatedJun 2, 2025
  • Python

[NAACL Findings 2025] Code and data of "Mitigating Hallucinations in Multimodal Spatial Relations through Constraint-Aware Prompting"

  • UpdatedMay 2, 2025
  • Python

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

  • UpdatedMay 28, 2025
  • Python

This repository contains all code to support the paper: "On the Importance of Text Preprocessing for Multimodal Representation Learning and Pathology Report Generation".

  • UpdatedJun 6, 2025
  • Jupyter Notebook

[ACL findings 2025] "Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models"

  • UpdatedJun 19, 2025
  • Python

Detecting Hallucinations in LLMs

  • UpdatedFeb 12, 2025
  • Python

An interactive Python chatbot demonstrating real-time contextual hallucination detection in Large Language Models using the "Lookback Lens" method. This project implements the attention-based ratio feature extraction and a trained classifier to identify when an LLM deviates from the provided context during generation.

  • UpdatedMay 16, 2025
  • Python

MedRAG-2 is an enhanced Retrieval-Augmented Generation pipeline that addresses the challenges of LLM hallucinations through prompt redesign of the MedRAG framework, enforcing strict grounding, structured output validation using Pydantic schemas, and cross-encoder based re-ranking for improved retrieval precision. KAUST's RAG Course.

  • UpdatedJul 9, 2025
  • Python

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