collaborators

9 papers

cs.LG2026

SPOT: Sparse Probing and Outcome Calibration for On-Policy Distillation

Zikun Qu, Min Zhang, Mingze Kong +5

On-policy distillation (OPD) provides dense teacher supervision on student-generated trajectories, but standard reverse-KL training can assign insufficient probability to other pla…

cs.AI2026

UniScale: Adaptive Unified Inference Scaling via Online Joint Optimization of Model Routing and Test-Time Scaling

Kaiyu Huang, Xingyu Wang, Mingze Kong +6

In real-world deployments of large language models (LLMs), balancing inference quality and computational cost has become a central challenge. Existing approaches tackle this trade-…

cs.LG2026

Linear and Neural Dueling Bandits with Delayed Feedback

Xiangyi Wang, Pingchen Lu, Jie Mao +4

Contextual dueling bandits form a cornerstone of preference-based decision-making, with critical applications in recommender systems and large language model alignment. However, st…

cs.AI2026

ALSO: Adversarial Online Strategy Optimization for Social Agents

Xiang Li, Liping Yi, Mingze Kong +3

Social simulation provides a compelling testbed for studying social intelligence, where agents interact through multi-turn dialogues under evolving contexts and strategically adapt…

cs.LG2026

MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks

Zhi Hong, Qian Zhang, Jiahang Sun +5

Large Language Models (LLMs) have achieved great success in many real-world applications, especially the one serving as the cognitive backbone of Multi-Agent Systems (MAS) to orche…

cs.AI2026

Workflow-R1: Group Sub-sequence Policy Optimization for Multi-turn Workflow Construction

Mingze Kong, Zikun Qu, Zhongquan Zhou +7

The rapid evolution of agentic workflows has demonstrated strong performance of LLM-based agents in addressing complex reasoning tasks. However, existing workflow optimization meth…