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Hallucination

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Showing 151–175 of 1816 papers

TitleStatusHype
Ornithologist: Towards Trustworthy "Reasoning" about Central Bank Communications—0
Prioritizing Image-Related Tokens Enhances Vision-Language Pre-TrainingCode0
Improving the Reliability of LLMs: Combining CoT, RAG, Self-Consistency, and Self-Verification—0
Adaptive Schema-aware Event Extraction with Retrieval-Augmented Generation—0
A Head to Predict and a Head to Question: Pre-trained Uncertainty Quantification Heads for Hallucination Detection in LLM OutputsCode1
On the Cost and Benefits of Training Context with Utterance or Full Conversation Training: A Comparative Stud—0
SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion—0
Multimodal Survival Modeling in the Age of Foundation ModelsCode0
Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning—0
TrumorGPT: Graph-Based Retrieval-Augmented Large Language Model for Fact-Checking—0
Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language ModelsCode1
Evolutionary thoughts: integration of large language models and evolutionary algorithmsCode0
Osiris: A Lightweight Open-Source Hallucination Detection System—0
Benchmarking LLM Faithfulness in RAG with Evolving LeaderboardsCode1
Mitigating Image Captioning Hallucinations in Vision-Language Models—0
Interpretable Zero-shot Learning with Infinite Class Concepts—0
UCSC at SemEval-2025 Task 3: Context, Models and Prompt Optimization for Automated Hallucination Detection in LLM OutputCode0
Invoke Interfaces Only When Needed: Adaptive Invocation for Large Language Models in Question AnsweringCode1
Knowledge Graphs for Enhancing Large Language Models in Entity Disambiguation—0
A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models—0
SEval-Ex: A Statement-Level Framework for Explainable Summarization Evaluation—0
Regression is all you need for medical image translationCode0
Multi-agents based User Values Mining for Recommendation—0
VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video UnderstandingCode1
Automated Parsing of Engineering Drawings for Structured Information Extraction Using a Fine-tuned Document Understanding Transformer—0
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