Papers by Bokai Hu

2 papers
Improving the Language Understanding Capabilities of Large Language Models Using Reinforcement Learning (2025.findings-emnlp)

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Challenge: Instruction-fine-tuned large language models (LLMs) under 14B parameters underperform on NLU tasks . we explore a framework to improve the NLU capabilities of LLMs .
Approach: They propose to use Proximal Policy Optimization to improve NLU capabilities . they frame NLU as a reinforcement learning environment and optimize for reward signals .
Outcome: The proposed framework outperforms supervised fine-tuning on GLUE and superGLUE tasks.
Enhancing Chat Language Models by Scaling High-quality Instructional Conversations (2023.emnlp-main)

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Challenge: a recent study validates the effectiveness of chat language models by fine-tuning instruction data.
Approach: They propose to use a large-scale dataset of instructional conversations to fine-tune a conversational model on instruction data.
Outcome: The proposed model outperforms open-source models in key metrics including scale, average length, diversity, coherence, etc.

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