activity
20242026
most citedEnabling Collaborative Clinical Diagnosis of Infectious Keratitis by Integrating Expert Knowledge and Interpretable Data-driven Intelligence

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Sibyl: An Efficient Small-large Model Collaboration Framework for Long-horizon Tasks

Zhewei Fang, Yuxin Zhang, Zhenwei Shao +8

Small language models (SLMs) offer a promising foundation for on-device agents through low-latency, resource-efficient inference, yet limited reasoning and planning capabilities co…

cs.CL2025

Tailoring Diagnostic Modeling to Individual Learners: Personalized Distractor Generation via MCTS-Guided Reasoning Reconstruction

Tao Wu, Jingyuan Chen, Wang Lin +6

Distractors-incorrect yet plausible answer choices in multiple-choice questions (MCQs)-are vital in educational assessments, as they help identify student misconceptions by present…

cs.AI2025

Contrastive Cross-Course Knowledge Tracing via Concept Graph Guided Knowledge Transfer

Wenkang Han, Wang Lin, Liya Hu +6

Knowledge tracing (KT) aims to predict learners' future performance based on historical learning interactions. However, existing KT models predominantly focus on data from a single…

cs.LG2025

Embracing Imperfection: Simulating Students with Diverse Cognitive Levels Using LLM-based Agents

Tao Wu, Jingyuan Chen, Wang Lin +5

Large language models (LLMs) are revolutionizing education, with LLM-based agents playing a key role in simulating student behavior. A major challenge in student simulation is mode…

cs.CV2024

Semantic Alignment for Multimodal Large Language Models

Tao Wu, Mengze Li, Jingyuan Chen +6

Research on Multi-modal Large Language Models (MLLMs) towards the multi-image cross-modal instruction has received increasing attention and made significant progress, particularly…

cs.AI2024★ 1 cited

Enabling Collaborative Clinical Diagnosis of Infectious Keratitis by Integrating Expert Knowledge and Interpretable Data-driven Intelligence

Zhengqing Fang, Shuowen Zhou, Zhouhang Yuan +9

Although data-driven artificial intelligence (AI) in medical image diagnosis has shown impressive performance in silico, the lack of interpretability makes it difficult to incorpor…