1 citations · 2 across the 11 of their papers we have counts for
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cs.IR2024★ 1 cited
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…
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…