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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 26–49 of 49 papers

TitleStatusHype
Real-Time Evaluation Models for RAG: Who Detects Hallucinations Best?—0
Instruction-Oriented Preference Alignment for Enhancing Multi-Modal Comprehension Capability of MLLMs—0
Evaluating LLMs' Assessment of Mixed-Context Hallucination Through the Lens of SummarizationCode0
TreeCut: A Synthetic Unanswerable Math Word Problem Dataset for LLM Hallucination EvaluationCode0
Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization—0
DAHL: Domain-specific Automated Hallucination Evaluation of Long-Form Text through a Benchmark Dataset in BiomedicineCode0
DDFAV: Remote Sensing Large Vision Language Models Dataset and Evaluation BenchmarkCode0
Unified Triplet-Level Hallucination Evaluation for Large Vision-Language ModelsCode0
A Survey of Hallucination in Large Visual Language Models—0
LongHalQA: Long-Context Hallucination Evaluation for MultiModal Large Language ModelsCode0
TLDR: Token-Level Detective Reward Model for Large Vision Language Models—0
Effectively Enhancing Vision Language Large Models by Prompt Augmentation and Caption UtilizationCode0
FIHA: Autonomous Hallucination Evaluation in Vision-Language Models with Davidson Scene Graphs—0
GraphEval: A Knowledge-Graph Based LLM Hallucination Evaluation Framework—0
Lynx: An Open Source Hallucination Evaluation Model—0
DefAn: Definitive Answer Dataset for LLMs Hallucination EvaluationCode0
HalluDial: A Large-Scale Benchmark for Automatic Dialogue-Level Hallucination EvaluationCode0
CHARP: Conversation History AwaReness Probing for Knowledge-grounded Dialogue Systems—0
TextSquare: Scaling up Text-Centric Visual Instruction Tuning—0
Can We Catch the Elephant? A Survey of the Evolvement of Hallucination Evaluation on Natural Language Generation—0
Exploring and Evaluating Hallucinations in LLM-Powered Code Generation—0
Hal-Eval: A Universal and Fine-grained Hallucination Evaluation Framework for Large Vision Language Models—0
Do Androids Know They're Only Dreaming of Electric Sheep?—0
ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks—0
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