109 citations · 232 across the 15 of their papers we have counts for
Showing 2024 · cs.CLShow all
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cs.CL2024
WarriorCoder: Learning from Expert Battles to Augment Code Large Language Models
Huawen Feng, Pu Zhao, Qingfeng Sun +8
Despite recent progress achieved by code large language models (LLMs), their remarkable abilities are largely dependent on fine-tuning on the high-quality data, posing challenges f…
cs.CL2024★ 1 cited
AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation
Mengkang Hu, Pu Zhao, Can Xu +5
Large Language Model-based agents have garnered significant attention and are becoming increasingly popular. Furthermore, planning ability is a crucial component of an LLM-based ag…
cs.CL2024★ 1 cited
Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena
Haipeng Luo, Qingfeng Sun, Can Xu +6
Assessing the effectiveness of large language models (LLMs) presents substantial challenges. The method of conducting human-annotated battles in an online Chatbot Arena is a highly…