most citedReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AI2024

ReasonAgain: Using Extractable Symbolic Programs to Evaluate Mathematical Reasoning

Xiaodong Yu, Ben Zhou, Hao Cheng +1

Existing math datasets evaluate the reasoning abilities of large language models (LLMs) by either using the final answer or the intermediate reasoning steps derived from static exa…

cs.CL2024

Model Tells Itself Where to Attend: Faithfulness Meets Automatic Attention Steering

Qingru Zhang, Xiaodong Yu, Chandan Singh +6

Large language models (LLMs) have demonstrated remarkable performance across various real-world tasks. However, they often struggle to fully comprehend and effectively utilize thei…

cs.CL2023★ 2 cited

ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks

Xiaodong Yu, Hao Cheng, Xiaodong Liu +2

Despite remarkable advancements in mitigating hallucinations in large language models (LLMs) by retrieval augmentation, it remains challenging to measure the reliability of LLMs us…