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Hallucination Evaluation

Evaluate the ability of LLM to generate non-hallucination text or assess the capability of LLM to recognize hallucinations.

Papers

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Showing 1–10 of 49 papers

TitleStatusHype
AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language ModelsCode3
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceCode2
HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language ModelsCode2
MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language ModelsCode2
HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language ModelsCode2
KnowRL: Exploring Knowledgeable Reinforcement Learning for FactualityCode1
Benchmarking LLM Faithfulness in RAG with Evolving LeaderboardsCode1
Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and MitigationCode1
Evaluating Image Hallucination in Text-to-Image Generation with Question-AnsweringCode1
Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language ModelsCode1
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