activity
20242026
collaborators

25 papers

cs.SE2026

SWE-Touch: Benchmarking Coding Agents When Users Touch the Code

Yuqiao Tan, Jinxiang Meng, Fangyu Lei +4

Real-world software development requires coding agents to operate in shared workspaces where users may inspect and modify code during an ongoing task, yet existing repository-level…

cs.CL2026

MemTools: A Unified Research Framework for Interoperable Agent Memory

Chengfeng Zhao, Jinhui Chen, Sirui Liang +4

While memory systems are essential for agent architectures, pervasive architectural fragmentation restricts systematic research. Existing implementations typically couple different…

cs.CL2026

Trace-Based On-Policy Distillation for Masked Diffusion Language Models

Haolin Ren, Ziyang Huang, Chenhao Yuan +2

Diffusion large language models (dLLMs) are a promising alternative to autoregressive generation. However, reasoning-oriented post-training for dLLMs remains challenging. Supervise…

cs.CL2026

Neural Procedural Memory: Empowering LLM Agents with Implicit Activation Steering

Chengfeng Zhao, Yuqiao Tan, Shizhu He +3

While Large Language Models (LLMs) excel as static solvers, transforming them into autonomous agents remains challenging. This transition requires continuous environmental interact…

cs.AI2026

SkillPyramid: A Hierarchical Skill Consolidation Framework for Self-Evolving Agents

Yuan Xiong, Ziqi Miao, Qian Chen +5

Recent AI agents can flexibly invoke skills to solve complex tasks, but their long-term improvement is fundamentally constrained by a lack of systematic skill construction, accumul…

cs.LG2026

Bottom-up Policy Optimization: Your Language Model Policy Secretly Contains Internal Policies

Yuqiao Tan, Minzheng Wang, Shizhu He +6

Existing reinforcement learning (RL) approaches treat large language models (LLMs) as a unified policy, overlooking their internal mechanisms. In this paper, we decompose the LLM-b…