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 31–40 of 49 papers

TitleStatusHype
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
PhD: A ChatGPT-Prompted Visual hallucination Evaluation DatasetCode1
DiaHalu: A Dialogue-level Hallucination Evaluation Benchmark for Large Language ModelsCode1
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceCode2
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
Alleviating Hallucinations of Large Language Models through Induced HallucinationsCode1
Mitigating Fine-Grained Hallucination by Fine-Tuning Large Vision-Language Models with Caption RewritesCode1
UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained GenerationCode1
Show:102550
← PrevPage 4 of 5Next →

No leaderboard results yet.