12 citations · 14 across the 10 of their papers we have counts for
10 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
RiTeK: A Dataset for Large Language Models Complex Reasoning over Textual Knowledge Graphs in Medicine
Jiatan Huang, Mingchen Li, Zonghai Yao +8
Answering complex real-world questions in the medical domain often requires accurate retrieval from medical Textual Knowledge Graphs (medical TKGs), as the relational path informat…
CancerLLM: A Large Language Model in Cancer Domain
Mingchen Li, Jiatan Huang, Jeremy Yeung +5
Medical Large Language Models (LLMs) have demonstrated impressive performance on a wide variety of medical NLP tasks; however, there still lacks a LLM specifically designed for phe…
Benchmarking Retrieval-Augmented Large Language Models in Biomedical NLP: Application, Robustness, and Self-Awareness
Mingchen Li, Zaifu Zhan, Han Yang +3
Large language models (LLM) have demonstrated remarkable capabilities in various biomedical natural language processing (NLP) tasks, leveraging the demonstration within the input c…