activity
20232026
most citedCollaborative Large Language Model for Recommender Systems

98 citations · 121 across the 21 of their papers we have counts for

collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL2026

TeacherGRPO: Closing the Capacity Gap in Reasoning Distillation via Teacher Alignment

Zhenyu Lei, Zihan Chen, Yaochen Zhu +5

Reasoning distillation from powerful teacher models to smaller students faces the Gap Curse: as teachers grow more sophisticated, their complex distributions increasingly diverge f…

cs.CL2026

IAPO: Information-Aware Policy Optimization for Token-Efficient Reasoning

Yinhan He, Yaochen Zhu, Mingjia Shi +5

Large language models increasingly rely on long chains of thought to improve accuracy, yet such gains come with substantial inference-time costs. We revisit token-efficient post-tr…

cs.CL2025

SemCoT: Accelerating Chain-of-Thought Reasoning through Semantically-Aligned Implicit Tokens

Yinhan He, Wendy Zheng, Yaochen Zhu +6

The verbosity of Chain-of-Thought (CoT) reasoning hinders its mass deployment in efficiency-critical applications. Recently, implicit CoT approaches have emerged, which encode reas…

cs.CL2025

Learning from Diverse Reasoning Paths with Routing and Collaboration

Zhenyu Lei, Zhen Tan, Song Wang +4

Advances in large language models (LLMs) significantly enhance reasoning capabilities but their deployment is restricted in resource-constrained scenarios. Knowledge distillation a…

cs.CL2024

Knowledge Graph-Enhanced Large Language Models via Path Selection

Haochen Liu, Song Wang, Yaochen Zhu +2

Large Language Models (LLMs) have shown unprecedented performance in various real-world applications. However, they are known to generate factually inaccurate outputs, a.k.a. the h…

cs.CL2023★ 5 cited

Knowledge Editing for Large Language Models: A Survey

Song Wang, Yaochen Zhu, Haochen Liu +3

Large language models (LLMs) have recently transformed both the academic and industrial landscapes due to their remarkable capacity to understand, analyze, and generate texts based…