activity
20242026
most citedMOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation

5 citations · 10 across the 12 of their papers we have counts for

collaborators

19 papers

cs.LG2026

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…

cs.AI2026

Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents

Zehong Wang, Fang Wu, Hongru Wang +8

Large language model (LLM)-based agents exhibit strong step-by-step reasoning capabilities over short horizons, yet often fail to sustain coherent behavior over long planning horiz…

cs.DL2026

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…

cs.LG2025

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…

cs.CL2025

AgentRouter: A Knowledge-Graph-Guided LLM Router for Collaborative Multi-Agent Question Answering

Zheyuan Zhang, Kaiwen Shi, Zhengqing Yuan +6

Large language models (LLMs) and agent-based frameworks have advanced rapidly, enabling diverse applications. Yet, with the proliferation of models and agentic strategies, practiti…

cs.CL2025

From Personal to Collective: On the Role of Local and Global Memory in LLM Personalization

Zehong Wang, Junlin Wu, ZHaoxuan Tan +4

Large language model (LLM) personalization aims to tailor model behavior to individual users based on their historical interactions. However, its effectiveness is often hindered by…