18 citations · 25 across the 9 of their papers we have counts for
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cs.CL2023★ 1 cited
Leveraging Structured Information for Explainable Multi-hop Question Answering and Reasoning
Ruosen Li, Xinya Du
Neural models, including large language models (LLMs), achieve superior performance on multi-hop question-answering. To elicit reasoning capabilities from LLMs, recent works propos…
cs.CV2023★ 2 cited
FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models
Liqiang Jing, Ruosen Li, Yunmo Chen +1
We introduce FaithScore (Faithfulness to Atomic Image Facts Score), a reference-free and fine-grained evaluation metric that measures the faithfulness of the generated free-form an…
cs.CL2023★ 18 cited
PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations
Ruosen Li, Teerth Patel, Xinya Du
Nowadays, the quality of responses generated by different modern large language models (LLMs) is hard to evaluate and compare automatically. Recent studies suggest and predominantl…