SOTAVerified

Hallucination Evaluation

Evaluate the ability of LLM to generate non-hallucination text or assess the capability of LLM to recognize hallucinations.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 21–30 of 49 papers

TitleStatusHype
UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained GenerationCode1
Exploring and Evaluating Hallucinations in LLM-Powered Code Generation—0
GraphEval: A Knowledge-Graph Based LLM Hallucination Evaluation Framework—0
Hal-Eval: A Universal and Fine-grained Hallucination Evaluation Framework for Large Vision Language Models—0
TextSquare: Scaling up Text-Centric Visual Instruction Tuning—0
TLDR: Token-Level Detective Reward Model for Large Vision Language Models—0
Localizing Before Answering: A Hallucination Evaluation Benchmark for Grounded Medical Multimodal LLMs—0
Lynx: An Open Source Hallucination Evaluation Model—0
A Survey of Hallucination in Large Visual Language Models—0
FIHA: Autonomous Hallucination Evaluation in Vision-Language Models with Davidson Scene Graphs—0
Show:102550
← PrevPage 3 of 5Next →

No leaderboard results yet.