collaborators

7 papers

cs.CL2026

RIVO: Lightweight Adaptive Rerouting for Deep Research Agents

Mingchen Li, Jiatan Huang, Hong Yu

Deep Research agents rely on long-horizon reasoning and iterative tool use to solve complex information-seeking tasks. However, adaptive decision-making over these trajectories rem…

cs.CL2026

OverdoseMoE: A Multi-Expert Framework for Opioid Overdose Risk Prediction

Mingchen Li, Rohan Pandey, Junhui Qian +5

Opioid overdose remains a major clinical and public health burden, highlighting the need for scalable approaches to identify patients at high risk. Here, we investigate diagnosis-s…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

RICE-PO: Turning Retrieval Interactions into Credit Signals for Reasoning Agents

Mingchen Li, Hansi Zeng, Zhuo Qian +4

Retrieval is increasingly moving from one-shot matching toward interactive reasoning, where language agents iteratively inspect evidence, reformulate queries, and search again. Tra…

cs.CL2026

Efficient and Effective Internal Memory Retrieval for LLM-Based Healthcare Prediction

Mingchen Li, Jiatan Huang, Zonghai Yao +1

Large language models (LLMs) hold significant promise for healthcare, yet their reliability in high-stakes clinical settings is often compromised by hallucinations and a lack of gr…

cs.CL2026

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…