Papers by Mingyi Jia
DDO: Dual-Decision Optimization for LLM-Based Medical Consultation via Multi-Agent Collaboration (2025.emnlp-main)
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| Challenge: | Existing LLMs fail to capture the dual nature of medical consultation (MC) this mismatch often results in ineffective symptom inquiry and unreliable disease diagnosis. |
| Approach: | They propose a novel LLM-based framework that performs Dual-Decision Optimization by decoupling the two sub-tasks and optimizing them with distinct objectives through a collaborative multi-agent workflow. |
| Outcome: | The proposed framework outperforms existing LLM-based approaches on three real-world MC datasets and achieves competitive performance with state-of-the-art generation-based methods. |
medIKAL: Integrating Knowledge Graphs as Assistants of LLMs for Enhanced Clinical Diagnosis on EMRs (2025.coling-main)
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| Challenge: | Electronic Medical Records (EMRs) are the digitized record of a patient's medical and health information and are integral to modern healthcare. |
| Approach: | They propose a framework that combines Large Language Models (LLMs) with knowledge graphs (KGs) to enhance diagnostic capabilities. |
| Outcome: | The proposed framework assigns weighted importance to entities in medical records based on their type, enabling precise localization of candidate diseases within KGs. |
BLUR: A Bi-Level Optimization Approach for LLM Unlearning (2026.eacl-long)
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Hadi Reisizadeh, Jinghan Jia, Zhiqi Bu, Bhanukiran Vinzamuri, Anil Ramakrishna, Kai-Wei Chang, Volkan Cevher, Sijia Liu, Mingyi Hong
| Challenge: | Existing algorithms to unlearn knowledge and capabilities from large datasets are unclear how to best formulate the unlearning problem. |
| Approach: | They propose to model the hierarchical structure of the unlearning problem, where the forget problem takes priority over the retain problem, and propose an algorithm that aims to unlearn knowledge and capabilities. |
| Outcome: | The proposed algorithm outperforms all state-of-the-art algorithms across unlearning tasks, models, and metrics. |