collaborators

9 papers

cs.AI2026

Fewer Tokens, Smaller Cache: Reward-Coordinated Efficient Reasoning

Qiyuan Zhu, Dezhi Li, Pengyu Cheng +8

Large Reasoning Models (LRMs) excel on complex tasks through long chain-of-thought (CoT) reasoning, but their lengthy intermediate steps cause severe overthinking that inflates inf…

cs.AI2026

The Curse of Helpfulness: Inverse Scaling Law in Robustness to Distractor Instructions via DistractionIF

Zeli Su, Zhankai Xu, Tianlei Chen +4

Large Language Models (LLMs) are increasingly deployed in agentic and retrieval-augmented generation (RAG) systems, where they must execute user-specified tasks over externally pro…

cs.AI2026

Counteraction-Aware Multi-Teacher On-Policy Distillation for General Capability Recovery with Domain Preservation

Tianlei Chen, Jiao Ou, Ziyuan Liu +3

Domain specialization can improve LLM behavior in vertical domains, but often weakens the general capabilities inherited from the original model. Recent Multi-Teacher On-Policy Dis…

cs.AI2026

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic

Shuo Liu, Tianle Chen, Ryan Amiri +1

Recent work has explored optimizing LLM collaboration through Multi-Agent Reinforcement Learning (MARL). However, most MARL fine-tuning approaches rely on predefined execution prot…

cs.CV2026

A Systematic Study of Cross-Modal Typographic Attacks on Audio-Visual Reasoning

Tianle Chen, Deepti Ghadiyaram

As audio-visual multi-modal large language models (MLLMs) are increasingly deployed in safety-critical applications, understanding their vulnerabilities is crucial. To this end, we…

cs.CV2026

VLM-UQBench: A Benchmark for Modality-Specific and Cross-Modality Uncertainties in Vision Language Models

Chenyu Wang, Tianle Chen, H. M. Sabbir Ahmad +2

Uncertainty quantification (UQ) is vital for ensuring that vision-language models (VLMs) behave safely and reliably. A central challenge is to localize uncertainty to its source, d…