up-to-date and curated list of awesome state-of-the-art LVLMs hallucinations research work, papers & resources
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Updated
Jun 5, 2024
up-to-date and curated list of awesome state-of-the-art LVLMs hallucinations research work, papers & resources
RefChecker provides automatic checking pipeline and benchmark dataset for detecting fine-grained hallucinations generated by Large Language Models.
[ACL 2024] An Easy-to-use Hallucination Detection Framework for LLMs.
Loki: Open-source solution designed to automate the process of verifying factuality
Knowledge Circuits in Pretrained Transformers
Official repo for the paper PHUDGE: Phi-3 as Scalable Judge. Evaluate your LLMs with or without custom rubric, reference answer, absolute, relative and much more. It contains a list of all the available tool, methods, repo, code etc to detect hallucination, LLM evaluation, grading and much more.
[NLPCC 2024] Shared Task 10: Regulating Large Language Models
Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models
[ACL 2024] Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation
Controlled HALlucination-Evaluation (CHALE) Question-Answering Dataset
openai assistant using code interpreter
[IJCAI 2024] FactCHD: Benchmarking Fact-Conflicting Hallucination Detection
Verify outputs generated by LLMs backed with real time data
This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strategy.
[NAACL24] Official Implementation of Mitigating Hallucination in Abstractive Summarization with Domain-Conditional Mutual Information
Code for ACL 2024 paper "TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space"
😎 up-to-date & curated list of awesome LMM hallucinations papers, methods & resources.
"Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases" by Jiarui Li and Ye Yuan and Zehua Zhang
[CVPR'24] HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
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