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hallucination detection

530 papers

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large language model (13587) retrieval-augmented generation (1592) text generation (2913) text classification (6793) uncertainty quantification (1393) natural language inference (1287) language model (4599) question answering (2963) benchmark evaluation (1556) fact verification (257)

Papers

Embedding and Gradient Say Wrong: A White-Box Method for Hallucination Detection EMNLP 2024
Decompose and Compare Consistency: Measuring VLMs’ Answer Reliability via Task-Decomposition Consistency Comparison EMNLP 2024
Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation EMNLP 2024
Pelican: Correcting Hallucination in Vision-LLMs via Claim Decomposition and Program of Thought Verification EMNLP 2024
ToolBeHonest: A Multi-level Hallucination Diagnostic Benchmark for Tool-Augmented Large Language Models EMNLP 2024
BrainLlama at SemEval-2024 Task 6: Prompting Llama to detect hallucinations and related observable overgeneration mistakes SEMEVAL 2024
RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models ACL 2024
The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ACL 2024
VisDiaHalBench: A Visual Dialogue Benchmark For Diagnosing Hallucination in Large Vision-Language Models ACL 2024
Analyzing LLM Behavior in Dialogue Summarization: Unveiling Circumstantial Hallucination Trends ACL 2024
Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification ACL 2024
Leveraging Entailment Judgements in Cross-Lingual Summarisation ACL 2024
A Comprehensive Survey of Hallucination in Large Language, Image, Video and Audio Foundation Models EMNLP 2024
Estimating the Hallucination Rate of Generative AI NIPS 2024
HalluSafe at SemEval-2024 Task 6: An NLI-based Approach to Make LLMs Safer by Better Detecting Hallucinations and Overgeneration Mistakes SEMEVAL 2024
NU-RU at SemEval-2024 Task 6: Hallucination and Related Observable Overgeneration Mistake Detection Using Hypothesis-Target Similarity and SelfCheckGPT SEMEVAL 2024
Byun at SemEval-2024 Task 6: Text Classification on Hallucinating Text with Simple Data Augmentation SEMEVAL 2024
DeepPavlov at SemEval-2024 Task 6: Detection of Hallucinations and Overgeneration Mistakes with an Ensemble of Transformer-based Models SEMEVAL 2024
Halu-NLP at SemEval-2024 Task 6: MetaCheckGPT - A Multi-task Hallucination Detection using LLM uncertainty and meta-models SEMEVAL 2024
SHROOM-INDElab at SemEval-2024 Task 6: Zero- and Few-Shot LLM-Based Classification for Hallucination Detection SEMEVAL 2024
SmurfCat at SemEval-2024 Task 6: Leveraging Synthetic Data for Hallucination Detection SEMEVAL 2024
AlphaIntellect at SemEval-2024 Task 6: Detection of Hallucinations in Generated Text SEMEVAL 2024
Contrastive Decoding Reduces Hallucinations in Large Multilingual Machine Translation Models EACL 2024
HypoTermQA: Hypothetical Terms Dataset for Benchmarking Hallucination Tendency of LLMs EACL 2024
Do Language Models Know When They’re Hallucinating References? EACL 2024