collaborators

9 papers

cs.SE2026

StaminaBench: Stress-Testing Coding Agents over 100 Interaction Turns

Vlad Sobal, Shuo Yang, Yuting Zhang +2

We introduce StaminaBench, a benchmark that measures the stamina of coding agents: how many consecutive interaction turns (change requests) they can handle before failing. Unlike t…

cs.LG2026

Reinforcement-aware Knowledge Distillation for LLM Reasoning

Zhaoyang Zhang, Shuli Jiang, Yantao Shen +6

Reinforcement learning (RL) post-training has recently driven major gains in long chain-of-thought reasoning large language models (LLMs), but the high inference cost of such model…

cs.LG2026

LLMZero: Discovering Adaptive Training Strategies for RL Post-Training via LLM Agents

Haoyang Fang, Wei Zhu, Boran Han +11

RL post-training strategies are dataset-dependent and reveal a recurring empirical pattern: capacity parameters accumulate monotonically across stages, while regularization paramet…

cs.CL2026

DLLG: Dynamic Logit-Level Gating of LLM Experts

Bingnan Li, Zhaoyang Zhang, Xiaoze Liu +6

Leveraging multiple specialized LLMs can combine complementary strengths, but existing approaches trade adaptability for stability: routing commits prematurely, heuristic ensemblin…

cs.CL2026

Consolidating Rewarded Perturbations for LLM Post-Training

Zheyu Zhang, Shuo Yang, Gjergji Kasneci

Post-training of language models is commonly framed as a sample-score-update loop implemented by gradient descent. A recent line of work, exemplified by RandOpt, relocates this loo…

cs.LG2026

EvoMAS: Evolutionary Generation of Multi-Agent Systems

Yuntong Hu, Yuting Zhang, Matthew Trager +4

Large language model (LLM)-based multi-agent systems (MAS) show strong promise for complex reasoning, planning, and tool-augmented tasks, but designing effective MAS architectures…