109 citations · 232 across the 15 of their papers we have counts for
4 papers · 1 filter
Towards a Unified Paradigm: Integrating Recommendation Systems as a New Language in Large Models
Kai Zheng, Qingfeng Sun, Can Xu +2
This paper explores the use of Large Language Models (LLMs) for sequential recommendation, which predicts users' future interactions based on their past behavior. We introduce a ne…
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…
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…
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…