222 citations · 614 across the 66 of their papers we have counts for
70 papers
BLADE: Auditing Information Use for Failure Attribution in LLM Multi-Agent Systems
Xiaoguang Guo, Yaohao Long, Chuxu Zhang
Large language model multi-agent systems extend individual agents' capabilities through collaboration across specialized roles, tools, and workflows. Yet collaboration makes failur…
MORL-A2C: Multi-Objective Reinforcement Learning Reranker for Optimizing Healthiness in MOPI-HFRS
Aarya Vasantlal, Joshua Zolla, Chuxu Zhang
Unhealthy dietary behavior continues to be a persistent public health issue in the United States, exacerbated by recommendation systems that prioritize user preference without cons…
SupraBench: A Benchmark for Supramolecular Chemistry
Tianyi Ma, Yijun Ma, Zehong Wang +6
Supramolecular chemistry, which includes the study of non-covalent host-guest assemblies, has advanced various applications. However, designing host-guest systems remains time-cons…
MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback
Zehong Wang, Yijun Ma, Connor R. Schmidt +7
Molecular dynamics (MD) is the canonical in-silico method for atomistic molecular science, simulating molecular behavior from first-principle physics. Designing an MD pipeline for…
ProPlay: Procedural World Models for Self-Evolving LLM Agents
Yijun Ma, Zehong Wang, Yiyang Li +5
Self-evolving agents are expected to improve through interaction without external supervision, but this remains difficult in partially observable environments where agents must exp…
Counterfactual Graph for Multi-Agent LLM Calibration
Jiatan Huang, Mingchen Li, Ziming Li +3
Multi-agent LLM systems often treat agreement as evidence: when many agents in a panel give the same answer, that answer is assumed to be more reliable. We show that this assumptio…
Where LLM Annotators Fail: Label-Free Learning on Graphs with LLMs
Safal Thapaliya, Jiatan Huang, Chuxu Zhang
Node classification on graphs often requires labeled nodes, yet obtaining labels at graph scale is expensive. When node attributes contain semantic content, such as paper abstracts…
In-Context Optimization for Retrieval-Augmented Generation: A Gradient-Descent Perspective
Mingchen Li, Jiatan Huang, Chuxu Zhang +2
In-context learning has recently been linked to implicit gradient descent in linear self-attention models, suggesting that context can induce a forward-pass update. Retrieval-augme…
Bridging Modalities, Spanning Time: Structured Memory for Ultra-Long Agentic Video Reasoning
Jiazheng Li, Chi-Hao Wu, Yunze Liu +3
Understanding ultra-long videos such as egocentric recordings, live streams, or surveillance footage spanning days to weeks, remains a challenge. For current multimodal LLMs: even…
Same Signal, Opposite Meaning: Direction-Informed Adaptive Learning for LLM Agents
Ziming Li, Jiatan Huang, Xiaoguang Guo +2
Adaptive test-time compute for LLM agents aims to invoke extra computation only when it improves performance. Existing methods typically use confidence-, uncertainty-, or difficult…
On the Safety of Graph Representation Learning
Xiaoguang Guo, Zehong Wang, Ziming Li +5
Graph representation learning (GRL) has evolved from topology-only graph embeddings to task-specific supervised GNNs, and more recently to reusable representations and graph founda…
EvolveRouter: Co-Evolving Routing and Prompt for Multi-Agent Question Answering
Jiatan Huang, Zheyuan Zhang, Kaiwen Shi +2
Large language model agents often exhibit complementary strengths, making routing a promising approach for multi-agent question answering. However, existing routing methods remain…
BHyGNN+: Unsupervised Representation Learning for Heterophilic Hypergraphs
Tianyi Ma, Yiyue Qian, Zehong Wang +3
Hypergraph Neural Networks (HyGNNs) have demonstrated remarkable success in modeling higher-order relationships among entities. However, their performance often degrades on heterop…
OPBench: A Graph Benchmark to Combat the Opioid Crisis
Tianyi Ma, Yiyang Li, Yiyue Qian +4
The opioid epidemic continues to ravage communities worldwide, straining healthcare systems, disrupting families, and demanding urgent computational solutions. To combat this letha…
Generalizing GNNs with Tokenized Mixture of Experts
Xiaoguang Guo, Zehong Wang, Jiazheng Li +5
Deployed graph neural networks (GNNs) are frozen at deployment yet must fit clean data, generalize under distribution shifts, and remain stable to perturbations. We show that stati…
Molecular Representations in Implicit Functional Space via Hyper-Networks
Zehong Wang, Xiaolong Han, Qi Yang +10
Molecular representations fundamentally shape how machine learning systems reason about molecular structure and physical properties. Most existing approaches adopt a discrete pipel…
GLEN-Bench: A Graph-Language based Benchmark for Nutritional Health
Jiatan Huang, Zheyuan Zhang, Tianyi Ma +4
Nutritional interventions are important for managing chronic health conditions, but current computational methods provide limited support for personalized dietary guidance. We iden…
LongDA: Benchmarking LLM Agents for Long-Document Data Analysis
Yiyang Li, Zheyuan Zhang, Tianyi Ma +4
We introduce LongDA, a data analysis benchmark for evaluating LLM-based agents under documentation-intensive analytical workflows. In contrast to existing benchmarks that assume we…
Graph is a Substrate Across Data Modalities
Ziming Li, Xiaoming Wu, Zehong Wang +6
Graphs provide a natural representation of relational structure that arises across diverse domains. Despite this ubiquity, graph structure is typically learned in a modality- and t…
Semantic Refinement with LLMs for Graph Representations
Safal Thapaliya, Zehong Wang, Jiazheng Li +3
Graph-structured data exhibit substantial heterogeneity in where their predictive signals originate: in some domains, node-level semantics dominate, while in others, structural pat…
GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
Xingbo Fu, Zhenyu Lei, Zihan Chen +3
Graph Neural Networks (GNNs) have revolutionized the field of graph learning by learning expressive graph representations from massive graph data. As a common pattern to train powe…
Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use
Yiyang Li, Zehong Wang, Zhengqing Yuan +4
Illicit drug use among teenagers and young adults (TYAs) remains a pressing public health concern, with rising prevalence and long-term impacts on health and well-being. To detect…
NG-Router: Graph-Supervised Multi-Agent Collaboration for Nutrition Question Answering
Kaiwen Shi, Zheyuan Zhang, Zhengqing Yuan +4
Diet plays a central role in human health, and Nutrition Question Answering (QA) offers a promising path toward personalized dietary guidance and the prevention of diet-related chr…
MAPRO: Recasting Multi-Agent Prompt Optimization as Maximum a Posteriori Inference
Zheyuan Zhang, Lin Ge, Hongjiang Li +3
Large language models (LLMs) have demonstrated remarkable capabilities across diverse tasks, and LLM-based agents further extend these abilities to various practical workflows. Whi…