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Home/Authors/Shumin Deng

Shumin Deng

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

NLP×3AI×3ML×3Multiagent×1Info Retrieval×1

Frequent co-authors

Zhuoyun Yu1×
Xin Xie1×
Wuguannan Yao1×
Chenxi Wang1×
Lei Liang1×
Xiang Qi1×

Research Timeline

2026
Exploring Autonomous Agentic Data Engineering for Model Specialization

The paper introduces Autonomous Agentic Data Engineering, demonstrating that LLMs can autonomously plan and optimize end-to-end data curation pipelines, leading to substantial performance gains in specialized models.

When Should Models Change Their Minds? Contextual Belief Management in Large Language Models

The paper introduces Contextual Belief Management (CBM) to address how LLMs should manage accumulating information over long interactions, showing that reinforcement learning significantly improves belief state accuracy.

SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories

SkillAdaptor is a novel, training-free framework that enables stable, step-level adaptation of external skills for LLM agents by precisely attributing failures to specific skills.

Highlighted terms show continued research focus across papers

Papers

cs.CLcs.AIcs.LGRecentMay 31, 2026

SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories

Zhuoyun Yu, Xin Xie, Wuguannan Yao, Chenxi Wang +3 more

SkillAdaptor is a novel, training-free framework that enables stable, step-level adaptation of external skills for LLM agents by precisely attributing failures to specific skills.

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cs.CLcs.AIcs.IRRecentMay 28, 2026

Exploring Autonomous Agentic Data Engineering for Model Specialization

Yujie Luo, Xiangyuan Ru, Jingsheng Zheng, Jingjing Wang +9 more

The paper introduces Autonomous Agentic Data Engineering, demonstrating that LLMs can autonomously plan and optimize end-to-end data curation pipelines, leading to substantial performance gains in spe…

View →
cs.AIcs.CLcs.LGRecentMay 28, 2026

When Should Models Change Their Minds? Contextual Belief Management in Large Language Models

Haoming Xu, Weihong Xu, Zongrui Li, Mengru Wang +5 more

The paper introduces Contextual Belief Management (CBM) to address how LLMs should manage accumulating information over long interactions, showing that reinforcement learning significantly improves be…

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