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Hallucination

Papers

Showing 12011225 of 1816 papers

TitleStatusHype
M2K-VDG: Model-Adaptive Multimodal Knowledge Anchor Enhanced Video-grounded Dialogue Generation0
Enabling Weak LLMs to Judge Response Reliability via Meta Ranking0
Reformatted AlignmentCode2
Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning0
EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language ModelsCode3
Aligning Modalities in Vision Large Language Models via Preference Fine-tuningCode2
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language ModelsCode1
LLMs in the Heart of Differential Testing: A Case Study on a Medical Rule Engine0
Using Hallucinations to Bypass GPT4's Filter0
Comparing Hallucination Detection Metrics for Multilingual Generation0
LLMDFA: Analyzing Dataflow in Code with Large Language ModelsCode3
Measuring and Reducing LLM Hallucination without Gold-Standard Answers0
Retrieve Only When It Needs: Adaptive Retrieval Augmentation for Hallucination Mitigation in Large Language Models0
Towards Uncovering How Large Language Model Works: An Explainability Perspective0
Trading off Consistency and Dimensionality of Convex Surrogates for the Mode0
EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language ModelsCode1
Uncertainty Quantification for In-Context Learning of Large Language ModelsCode1
Do LLMs Know about Hallucination? An Empirical Investigation of LLM's Hidden States0
Visually Dehallucinative Instruction Generation: Know What You Don't KnowCode0
Into the Unknown: Self-Learning Large Language ModelsCode1
Large Language Model with Graph Convolution for Recommendation0
LLMAuditor: A Framework for Auditing Large Language Models Using Human-in-the-Loop0
InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference AlignmentCode2
Visually Dehallucinative Instruction GenerationCode0
Mitigating Object Hallucination in Large Vision-Language Models via Classifier-Free Guidance0
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