29 citations · 97 across the 89 of their papers we have counts for
90 papers
Leveraging Inference-Time Compute for Diffusion Models via Global Scheduling of Denoising Trajectories
Yuan Cao, Yifu Tang, Hangqi Li +1
Diffusion models generate a sample by traversing a denoising trajectory, a sequence of stochastic noise-reduction steps that transforms pure noise into a draw from a target distrib…
Spec2Twin-Chain: Orchestrating Bi-Level Optimization with LLMs for Blockchain Digital Twin Construction
Haoting Zhang, Haoxian Chen, Jiayuan Sheng +4
Building a blockchain digital twin largely requires translating domain knowledge and specific system descriptions into a simulator architecture, calibrating its parameters against…
3D-DefectBench: A Controlled Factorial Study of Vision-Language Model Evaluation Pipelines for Fine-Grained 3D Generation Defects
Zhenyu Zhao, Nanshan Jia, Jihyeon Je +7
Automated evaluation is essential for scaling generative 3D systems, where exhaustive human review is costly and slow. Yet the reliability of an automated judge depends on the full…
ClawArena-Team: Benchmarking Subagent Orchestration and Dynamic Workflows in Language-Model Agents
Kaiwen Xiong, Haonian Ji, Shi Qiu +4
Production large language-model (LLM) agents are increasingly deployed not as lone problem-solvers but as managers: a main model creates specialized subagents, delegates work, and…
HERO: Improving the Reliability and Sensitivity of Generative Model Evaluation Using Historical Data
Xinrui Ruan, Zhenyu Zhao, Waverly Wei +4
Reliable generative AI models critically rely on expert human annotations to evaluate output quality, yet these "gold" labels are expensive to collect and limited in quantity. Orga…
VisualClaw: A Real-Time, Personalized Agent for the Physical World
Haoqin Tu, Jianwen Chen, Zijun Wang +14
Vision language models are serving as general-purpose interfaces for complex multimodal tasks. However, deployment still faces three gaps: VLMs typically incur high latency and cos…
Experimentation for Different Scheduling Policies on Queues: Mixed Differences-in-Q Estimators Based on Little's Law
Nanshan Jia, Ramesh Johari, Nian Si +1
In data centers, tasks are dispatched to various servers to evenly distribute the workload. When a data center considers implementing a new scheduling algorithm, it typically condu…
DB-3DME: From Dataset to Benchmark for Human-aligned Automatic 3D Mesh Evaluation
Nanshan Jia, Zhenyu Zhao, Sui Huang +3
Recent advances in 3D generation have led to substantial improvements in realism, controllability, and efficiency, yet the evaluation of 3D assets remains underexplored. Existing e…
Hypothesis-Disciplined Multi-Agent Automated Formalization of Asymptotic Statistical Theory
Tingzhou Wei, Zeyu Zheng, Ethan X. Fang +1
Asymptotic statistical theory is a challenging domain for AI-assisted formalization: its central results mix convergence statements, asymptotic expansions, functional analysis, and…
AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration
Jiaqi Liu, Shi Qiu, Mairui Li +33
Automating scientific discovery requires more than generating papers from ideas. Real research is iterative: hypotheses are challenged from multiple perspectives, experiments fail…
ClawForge: Generating Executable Interactive Benchmarks for Command-Line Agents
Yuxiang Lai, Peng Xia, Haonian Ji +8
Interactive agent benchmarks face a tension between scalable construction and realistic workflow evaluation. Hand-authored tasks are expensive to extend and revise, while static pr…
ClawArena: Benchmarking AI Agents in Evolving Information Environments
Haonian Ji, Kaiwen Xiong, Siwei Han +9
AI agents deployed as persistent assistants must maintain correct beliefs as their information environment evolves. In practice, evidence is scattered across heterogeneous sources…
Contexting as Recommendation: Evolutionary Collaborative Filtering for Context Engineering
Jiachen Zhu, Zhuoying Ou, Congmin Zheng +9
Large Language Models (LLMs) are highly sensitive to their input contexts, motivating the development of automated context engineering. However, existing methods predominantly trea…
EvolveMem:Self-Evolving Memory Architecture via AutoResearch for LLM Agents
Jiaqi Liu, Xinyu Ye, Peng Xia +4
Long-term memory is essential for LLM agents that operate across multiple sessions, yet existing memory systems treat retrieval infrastructure as fixed: stored content evolves whil…
Selection of the Best Policy under Fairness Constraints for Subpopulations
Tingyu Zhu, Yuhang Wu, Zeyu Zheng
Many high-stakes decisions in health care, public policy, and clinical development require committing to a single policy that will be applied uniformly across a heterogeneous popul…
Position: Academic Conferences are Potentially Facing Denominator Gaming Caused by Fully Automated Scientific Agents
Rong Shan, Te Gao, Hang Zheng +6
The implicit policy of maintaining relatively stable acceptance rates at top AI conferences, despite exponentially growing submissions, introduces a critical structural vulnerabili…
ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker Agents
Fanqing Meng, Lingxiao Du, Zijian Wu +46
Language-model agents are increasingly used as persistent coworkers that assist users across multiple working days. During such workflows, the surrounding environment may change in…
VLAA-GUI: Knowing When to Stop, Recover, and Search, A Modular Framework for GUI Automation
Qijun Han, Haoqin Tu, Zijun Wang +11
Autonomous GUI agents face two fundamental challenges: early stopping, where agents prematurely declare success without verifiable evidence, and repetitive loops, where agents cycl…
Bilevel Optimization of Agent Skills via Monte Carlo Tree Search
Chenyi Huang, Haoting Zhang, Jingxu Xu +2
Agent \texttt{skills} are structured collections of instructions, tools, and supporting resources that help large language model (LLM) agents perform particular classes of tasks. E…
Grid2Matrix: Revealing Digital Agnosia in Vision-Language Models
Yunkai Zhang, Linda Li, Yingxin Cui +5
Vision-Language Models (VLMs) excel on many multimodal reasoning benchmarks, but these evaluations often do not require an exhaustive readout of the image and can therefore obscure…
Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering
Chenyu Zhou, Huacan Chai, Wenteng Chen +18
Large language model (LLM) agents are increasingly built less by changing model weights than by reorganizing the runtime around them. Capabilities that earlier systems expected the…
Your Agent, Their Asset: A Real-World Safety Analysis of OpenClaw
Zijun Wang, Haoqin Tu, Letian Zhang +11
OpenClaw, the most widely deployed personal AI agent in early 2026, operates with full local system access and integrates with sensitive services such as Gmail, Stripe, and the fil…
Omni-SimpleMem: Autoresearch-Guided Discovery of Lifelong Multimodal Agent Memory
Jiaqi Liu, Zipeng Ling, Shi Qiu +9
AI agents increasingly operate over extended time horizons, yet their ability to retain, organize, and recall multimodal experiences remains a critical bottleneck. Building effecti…
AdaExplore: Failure-Driven Adaptation and Diversity-Preserving Search for Efficient Kernel Generation
Weihua Du, Jingming Zhuo, Yixin Dong +9
Recent large language model (LLM) agents have shown promise in using execution feedback for test-time adaptation. However, robust self-improvement remains far from solved: most app…