156 citations · 356 across the 18 of their papers we have counts for
5 papers · 1 filter
Chain-of-Thought Hub: A Continuous Effort to Measure Large Language Models' Reasoning Performance
Yao Fu, Litu Ou, Mingyu Chen +3
As large language models (LLMs) are continuously being developed, their evaluation becomes increasingly important yet challenging. This work proposes Chain-of-Thought Hub, an open-…
Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback
Yao Fu, Hao Peng, Tushar Khot +1
We study whether multiple large language models (LLMs) can autonomously improve each other in a negotiation game by playing, reflecting, and criticizing. We are interested in this…
Specializing Smaller Language Models towards Multi-Step Reasoning
Yao Fu, Hao Peng, Litu Ou +2
The surprising ability of Large Language Models (LLMs) to perform well on complex reasoning with only few-shot chain-of-thought prompts is believed to emerge only in very large-sca…
HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization
Zhongfen Deng, Hao Peng, Dongxiao He +2
The current state-of-the-art model HiAGM for hierarchical text classification has two limitations. First, it correlates each text sample with all labels in the dataset which contai…
Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation
Zhongfen Deng, Hao Peng, Congying Xia +3
Review rating prediction of text reviews is a rapidly growing technology with a wide range of applications in natural language processing. However, most existing methods either use…