18 citations · 37 across the 29 of their papers we have counts for
10 papers · 1 filter
BrainLinear: A Linear Model for Brain Network Analysis in Sparse Tangent Subspaces
Sijing Wu, Dongyuan Li, Miaoting Huang +4
Functional connectome analysis examines brain-region interactions to understand and identify disorders such as autism spectrum disorder and Alzheimer's disease. Existing methods ty…
HarnessSafe: Evaluating Safety Across Persistent Carriers in Agent Harnesses
Xiao Zhang, Yusheng Wang, Yuhao Fei +5
Modern agent harnesses persist state across tasks and sessions through persistent carriers like memory, skills, tools, and shared artifacts. However, this capability creates delaye…
Can LLM design high-quality experiments? A Comprehensive and Systematic Benchmark on Autonomous Experimental Design
Zejun Liu, Jian Wu, Ru Peng +4
AI for Research (AI4Research) leverages AI to automate and improve scientific workflows. While experimental design is a critical stage of the research process, prior work has focus…
HAS-Bench: Evaluating LLM-Based Human-Agent Systems under Configurable Human Participation
Yaozu Wu, Wei-Chieh Huang, Jizhou Guo +11
Large language models increasingly operate in settings where humans are active collaborators rather than passive task providers. We introduce HAS-Framework, a graph-based framework…
PaperClaw: Harnessing Agents for Autonomous Research and Human-in-the-Loop Refinement
Weiwei Ye, Hangchen Liu, Dongyuan Li +1
Large language models have become capable reasoners and tool users that write and run code and search the literature, which makes automating the research process itself a realistic…
TimeClaw: A Time-Series AI Agent with Exploratory Execution Learning
Hangchen Liu, Dongyuan Li, Renhe Jiang +3
Time series analysis underpins forecasting, monitoring, and decision making in domains such as finance and weather, where solving a task often requires both numerical accuracy and…
Node Role-Guided LLMs for Dynamic Graph Clustering
Dongyuan Li, Ying Zhang, Yaozu Wu +1
Dynamic graph clustering aims to detect and track time-varying clusters in dynamic graphs, revealing how complex real-world systems evolve over time. However, existing methods are…
Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral Decomposition
Dongyuan Li, Shun Zheng, Chang Xu +2
Time series forecasting has attracted significant attention in the field of AI. Previous works have revealed that the Channel-Independent (CI) strategy improves forecasting perform…
ELLMob: Event-Driven Human Mobility Generation with Self-Aligned LLM Framework
Yusong Wang, Chuang Yang, Jiawei Wang +5
Human mobility generation aims to synthesize plausible trajectory data, which is widely used in urban system research. While Large Language Model-based methods excel at generating…
See2Refine: Vision-Language Feedback Improves LLM-Based eHMI Action Designers
Ding Xia, Xinyue Gui, Mark Colley +5
Automated vehicles lack natural communication channels with other road users, making external Human-Machine Interfaces (eHMIs) essential for conveying intent and maintaining trust…