collaborators

25 papers

cs.AI2026

XBridge: Entity-Grounded Latent Bridge for Heterogeneous LLM Communication

Wooseong Yang, Wei-Chieh Huang, Weizhi Zhang +3

Heterogeneous multi-agent LLM systems, where agents are powered by different model families, can outperform homogeneous configurations by reducing redundant reasoning patterns. Yet…

cs.IR2026

Personalized Recommendation Tool Learning via Autonomous Language Agents

Mingdai Yang, Zhiwei Liu, Weizhi Zhang +3

Although large language models (LLMs) have recently gained traction in recommender systems due to their strong reasoning capabilities and extensive world knowledge, previous LLM-ba…

cs.LG2026

BlockServe: Block-Grained Continuous Batching for High-Throughput Diffusion LLM Serving

Yuanjie Zhu, Liangwei Yang, Ke Xu +4

Efficient serving of diffusion large language models (dLLMs) is hindered by convergence heterogeneity: when batching multiple requests, different sequences converge at different ra…

cs.CL2026

RubricsTree: Scalable and Evolving Open-Ended Evaluation of Personal Health Agents across Health Memory and Medical Skills

Weizhi Zhang, Zechen Li, Hamid Palangi +16

The LLM-empowered personal health agents with user health (sensor) metrics have offered a promising pathway to alleviate global disparities in healthcare access. However, large-sca…

cs.IR2026

Toward User Preference Alignment in LLM Recommendation via Explicit Context Feedback

Weizhi Zhang, Wooseong Yang, Yuxin Cui +9

Traditional recommender systems (RecSys) primarily infer user preferences from implicit signals (such as clicks, watches, and purchases), often neglecting the rich explicit context…

cs.CL2026

SciCustom: A Framework for Custom Evaluation of Scientific Capabilities in Large Language Models

Yiyang Gu, Junwei Yang, Junyu Luo +15

Large language models (LLMs) are increasingly applied to scientific research, yet existing evaluations often fail to reflect the fine-grained capabilities required in practice. Mos…