21 citations · 74 across the 16 of their papers we have counts for
Showing 2024 · cs.CLShow all
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cs.CL2024
Nuance Matters: Probing Epistemic Consistency in Causal Reasoning
Shaobo Cui, Junyou Li, Luca Mouchel +2
To address this gap, our study introduces the concept of causal epistemic consistency, which focuses on the self-consistency of Large Language Models (LLMs) in differentiating inte…
cs.CL2024
Improving Sample Efficiency of Reinforcement Learning with Background Knowledge from Large Language Models
Fuxiang Zhang, Junyou Li, Yi-Chen Li +3
Low sample efficiency is an enduring challenge of reinforcement learning (RL). With the advent of versatile large language models (LLMs), recent works impart common-sense knowledge…
cs.CL2024★ 21 cited
More Agents Is All You Need
Junyou Li, Qin Zhang, Yangbin Yu +2
We find that, simply via a sampling-and-voting method, the performance of large language models (LLMs) scales with the number of agents instantiated. Also, this method, termed as A…