collaborators

26 papers

cs.LG2026

SAF-OPD: Stable Advantage Fusion for On-Policy Distillation

Yifan Ding, Xincheng Wei, Yoshua Y. Li +7

Reinforcement learning with verifiable rewards (RLVR) broadcasts a single response-level reward to every token, while on-policy distillation (OPD) scores each token against a stron…

cs.AI2026

ACE: Pluggable Adaptive Context Elasticizer across Agents

Ning Liao, Zihao Long, Xiaoxing Wang +6

The increasing complexity of agentic tasks has led to rapidly growing trajectory lengths, which poses significant challenges for large language model (LLM) based agents with fixed…

cs.AI2026

CuraWeb: Joint Optimization of Quality, Redundancy, and Diversity for Web-Scale Pretraining Data

Peiguang Li, Yongwei Zhou, Juncheng Diao +12

Open-web corpora curated via highly selective filters, such as FineWeb-Edu and DCLM, constitute the core of LLM pretraining data and have significantly advanced LLM performance. Ho…

cs.AI2026

HIPIF: Hierarchical Planning and Information Folding for Long-Horizon LLM Agent Learning

Juncheng Diao, Zhicong Lu, Peiguang Li +6

While Large Language Models (LLMs) have demonstrated strong capabilities as autonomous agents across a wide range of tasks, their performance often degrades in multi-turn long-hori…

cs.CL2026

Predictable Scaling Laws of Optimal Hyperparameters for LLM Continued Pre-training

Yongwei Zhou, Juncheng Diao, Junlin Shang +2

The efficacy of continued pre-training for Large Language Models (LLMs) hinges upon hyperparameter configurations, such as learning rate and batch size. However, current practices…

cs.CL2026

Prefix Teach, Suffix Fade: Local Teachability Collapse in Strong-to-Weak On-Policy Distillation

Kaiyuan Liu, Ziyuan Zhuang, Yang Bai +3

On-policy distillation (OPD) trains a student model on its own rollouts using dense feedback from a stronger teacher. Prior literature suggests that, provided teacher feedback is a…