2 citations · 3 across the 15 of their papers we have counts for
19 papers
Not All Criteria Matter: Importance-Aware Criteria Weighting for Rubric-Based LLM Evaluation
Haocheng Yang, Licheng Pan, Yiming Dong +7
Rubric-based evaluation assesses the responses of large language models (LLMs) by aggregating the verification results of explicit criteria, yet not all criteria matter equally. Ho…
PhysCodeGym: Benchmarking Coding Agents for Physically Verifiable 4D Reconstruction
Shuai Shao, Jinchen He, Cunxin Fan +10
Building physical simulations from video requires coding agents to translate observations into executable models and refine them through tool use. We introduce PhysCodeGym, a bench…
MCPDisCo: Seesaw-Mitigated Tuning for MCP-Native Agents
Kounianhua Du, Jianxing Liu, Shuai Shao +3
The Model Context Protocol provides a shared interaction substrate for the agentic web, allowing heterogeneous services to expose capabilities through a standardized interface. Lea…
RubricArmor: Adversarial Evolution Improves LLM-Based Rubric Generation
Haocheng Yang, Yuchao Zhang, Licheng Pan +8
Rubric-based reinforcement learning (RL) provides interpretable rewards for aligning large language models (LLMs) by evaluating responses against query-specific evaluation criteria…
SkillGate: Training In-Policy Skill Selection in Long-Horizon Agents
Qingyao Li, Wenxiang Jiao, Shuai Shao +6
Agent frameworks increasingly package procedural knowledge as skills: instruction files an agent reads on demand, while public libraries now hold thousands of them. Which skill to…
MedClaw: Heuristic Agent Harness for Long-Horizon Surgical Video Reasoning
Yingying Fan, Penghui Du, Leyan Zhu +10
Understanding tens-of-minutes surgical videos requires long-horizon temporal reasoning, answering what happens before, after, or across stages of a procedure by grounding the quest…
Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories
Shuai Shao, Kangning Zhang, Qingyao Li +7
Agents built around large language models continually accumulate interaction trajectories during deployment, yet their behavior typically remains fixed. Beyond updating model weigh…
VAD: Attributing Visual Evidence for Target Reconstruction in Multimodal On-Policy Distillation
Kangning Zhang, Yixing Li, Shuai Shao +9
Multimodal on-policy distillation (OPD) transfers fine-grained visual knowledge by supervising student-generated trajectories with a privileged-view teacher. Yet its next-token cor…
ACM: Agentic Context Management for Long Horizon Tasks
Xiaochuan Li, Ryan Ming, Meng Chu +3
Agentic tasks are inherently long-horizon and multi-turn, constantly accumulating context through interactions with the environment. Existing context compression methods inevitably…
Clarus: Coordinating Autonomous Research Agents toward Web-Scale Scientific Collaboration
Zihan Guo, Zeyi Chen, Zhiyu Chen +15
Existing autonomous research agents can support parts of the research process, but most systems still treat research as either an isolated assistant task or a closed workflow. Ther…
MMSkills: Towards Multimodal Skills for General Visual Agents
Kangning Zhang, Shuai Shao, Qingyao Li +8
Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as textual prompts, executable co…
AgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Security
Dongrui Liu, Yu Li, Zhonghao Yang +47
Modern open-world agents such as OpenClaw exhibit powerful cross-environment execution capabilities yet introduce broad new safety risk sources. Meanwhile, advanced frontier AI mod…
VisionCreator: A Native Visual-Generation Agentic Model with Understanding, Thinking, Planning and Creation
Jinxiang Lai, Zexin Lu, Jiajun He +11
Visual content creation tasks demand a nuanced understanding of design conventions and creative workflows-capabilities challenging for general models, while workflow-based agents l…
Code2Math: Can Your Code Agent Evolve Math Problems Through Exploration?
Dadi Guo, Yuejin Xie, Qingyu Liu +11
As large language models (LLMs) advance their mathematical capabilities toward the IMO and research level, the scarcity of challenging, high-quality problems has become a significa…
Evaluating Test-Time Scaling of General LLM Agents
Xiaochuan Li, Ryan Ming, Pranav Setlur +6
LLM agents are increasingly expected to operate as general-purpose systems that resolve real-world user requests, yet their dynamic scaling behavior in realistic environments remai…
Luna-2: Scalable Single-Token Evaluation with Small Language Models
Vatsal Goel, Rishon Dsouza, Nikhil Ega +4
Real-time guardrails require evaluation that is accurate, cheap, and fast - yet today's default, LLM-as-a-judge (LLMAJ), is slow, expensive, and operationally non-deterministic due…
MonoScale: Scaling Multi-Agent System with Monotonic Improvement
Shuai Shao, Yixiang Liu, Bingwei Lu +1
In recent years, LLM-based multi-agent systems (MAS) have advanced rapidly, using a router to decompose tasks and delegate subtasks to specialized agents. A natural way to expand c…
Your Agent May Misevolve: Emergent Risks in Self-evolving LLM Agents
Shuai Shao, Qihan Ren, Chen Qian +8
Advances in Large Language Models (LLMs) have enabled a new class of self-evolving agents that autonomously improve through interaction with the environment, demonstrating strong c…
AgentNet: Decentralized Evolutionary Coordination for LLM-based Multi-Agent Systems
Yingxuan Yang, Huacan Chai, Shuai Shao +4
The rapid advancement of large language models (LLMs) has enabled the development of multi-agent systems where multiple LLM-based agents collaborate on complex tasks. However, exis…