58 citations · 82 across the 56 of their papers we have counts for
26 papers · 1 filter
Humanly: A Configurable and Traceable Environment for Human-AI Collaborative Writing
Shenzhe Zhu, Haoqian Zhang, Xu Yang +7
Teachers, conference chairs, and public readers all judge writing from limited evidence, seeing only a finished document and not the process that produced it. Final text alone cann…
ProACT: Towards Breakdown-Aware Proactive Agent in Multi-User Collaboration
Shu Yang, Difei Xu, Jiaxin Pei +1
Conversational agents are increasingly embedded in human collaborative work, yet they remain fundamentally passive and reactive: they respond to explicit user requests rather than…
SelfMem: Self-Optimizing Memory for AI Agents
Shu Yang, Junchao Wu, Derek F. Wong +1
While current AI agents support increasingly long context windows, tool use, and skill execution for long-horizon tasks, they still require memory systems to effectively leverage h…
Multi-User Large Language Model Agents
Shu Yang, Shenzhe Zhu, Hao Zhu +5
Large language models (LLMs) and LLM-based agents are increasingly deployed as assistants in planning and decision making, yet most existing systems are implicitly optimized for a…
Hierarchical Alignment: Enforcing Hierarchical Instruction-Following in LLMs through Logical Consistency
Shu Yang, Zihao Zhou, Di Wang +1
Large language models increasingly operate under multiple instructions from heterogeneous sources with different authority levels, including system policies, user requests, tool ou…
Neuron-Aware Data Selection In Instruction Tuning For Large Language Models
Xin Chen, Junchao Wu, Shu Yang +6
Instruction Tuning (IT) has been proven to be an effective approach to unlock the powerful capabilities of large language models (LLMs). Recent studies indicate that excessive IT d…