collaborators

5 papers

cs.AI2026

Lifting Traces to Logic: Programmatic Skill Induction with Neuro-Symbolic Learning for Long-Horizon Agentic Tasks

Jie-Jing Shao, Haiyan Yin, Yueming Lyu +5

Foundation model-driven agents often struggle with long-horizon planning due to the transient nature of purely prompting-based reasoning. While existing skill induction methods mit…

cs.RO2026

SA-VLA: Spatially-Aware Flow-Matching for Vision-Language-Action Reinforcement Learning

Xu Pan, Zhenglin Wan, Xingrui Yu +6

Vision-Language-Action (VLA) models exhibit strong generalization in robotic manipulation, yet reinforcement learning (RL) fine-tuning often degrades robustness under spatial distr…

cs.CL2026

Time-Annealed Perturbation Sampling: Diverse Generation for Diffusion Language Models

Jingxuan Wu, Zhenglin Wan, Xingrui Yu +4

Diffusion language models (Diffusion-LMs) introduce an explicit temporal dimension into text generation, yet how this structure can be leveraged to control generation diversity for…

cs.CR2025

Reflection-Driven Control for Trustworthy Code Agents

Bin Wang, Jiazheng Quan, Xingrui Yu +3

Contemporary large language model (LLM) agents are remarkably capable, but they still lack reliable safety controls and can produce unconstrained, unpredictable, and even actively…

cs.CL2025

UniErase: Towards Balanced and Precise Unlearning in Language Models

Miao Yu, Liang Lin, Guibin Zhang +7

Large language models (LLMs) require iterative updates to address the outdated information problem, where LLM unlearning offers an approach for selective removal. However, mainstre…