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Hallucination Evaluation
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Evaluate the ability of LLM to generate non-hallucination text or assess the capability of LLM to recognize hallucinations.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality
MultiHal: Multilingual Dataset for Knowledge-Graph Grounded Evaluation of LLM Hallucinations
Benchmarking LLM Faithfulness in RAG with Evolving Leaderboards
Mitigating Image Captioning Hallucinations in Vision-Language Models
Localizing Before Answering: A Hallucination Evaluation Benchmark for Grounded Medical Multimodal LLMs
Real-Time Evaluation Models for RAG: Who Detects Hallucinations Best?
Instruction-Oriented Preference Alignment for Enhancing Multi-Modal Comprehension Capability of MLLMs
Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and Mitigation
Evaluating LLMs' Assessment of Mixed-Context Hallucination Through the Lens of Summarization
TreeCut: A Synthetic Unanswerable Math Word Problem Dataset for LLM Hallucination Evaluation
Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
DAHL: Domain-specific Automated Hallucination Evaluation of Long-Form Text through a Benchmark Dataset in Biomedicine
DDFAV: Remote Sensing Large Vision Language Models Dataset and Evaluation Benchmark
Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Models
A Survey of Hallucination in Large Visual Language Models
LongHalQA: Long-Context Hallucination Evaluation for MultiModal Large Language Models
TLDR: Token-Level Detective Reward Model for Large Vision Language Models
Effectively Enhancing Vision Language Large Models by Prompt Augmentation and Caption Utilization
FIHA: Autonomous Hallucination Evaluation in Vision-Language Models with Davidson Scene Graphs
Evaluating Image Hallucination in Text-to-Image Generation with Question-Answering
Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models
Enhancing LLM's Cognition via Structurization
GraphEval: A Knowledge-Graph Based LLM Hallucination Evaluation Framework
Lynx: An Open Source Hallucination Evaluation Model
AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models
DefAn: Definitive Answer Dataset for LLMs Hallucination Evaluation
HalluDial: A Large-Scale Benchmark for Automatic Dialogue-Level Hallucination Evaluation
CHARP: Conversation History AwaReness Probing for Knowledge-grounded Dialogue Systems
TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Can We Catch the Elephant? A Survey of the Evolvement of Hallucination Evaluation on Natural Language Generation
Exploring and Evaluating Hallucinations in LLM-Powered Code Generation
PhD: A ChatGPT-Prompted Visual hallucination Evaluation Dataset
DiaHalu: A Dialogue-level Hallucination Evaluation Benchmark for Large Language Models
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space
Hal-Eval: A Universal and Fine-grained Hallucination Evaluation Framework for Large Vision Language Models
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