activity
20232026
collaborators

5 papers

cs.AI2026

Evo-PI: Aligning Medical Reasoning via Evolving Principle-Guided Supervision

Xianda Zheng, Huan Gao, Meng-Fen Chiang +3

Despite recent progress, the reasoning capabilities of large multimodal language models (MLLMs) remain fundamentally constrained by static supervision, where fixed prompts, rules,…

cs.AI2025

Disentangling Reasoning Logic to Resolve Explicit Knowledge Conflicts

Xianda Zheng, Zijian Huang, Meng-Fen Chiang +4

Explicit knowledge conflicts, occurring when retrieved contexts contain contradictory information, pose a fundamental challenge for Large Language Models (LLMs) as they integrate i…

cs.LG2023

SGA: A Graph Augmentation Method for Signed Graph Neural Networks

Zeyu Zhang, Shuyan Wan, Sijie Wang +5

Signed Graph Neural Networks (SGNNs) are vital for analyzing complex patterns in real-world signed graphs containing positive and negative links. However, three key challenges hind…

cs.LG2023

Enhancing Signed Graph Neural Networks through Curriculum-Based Training

Zeyu Zhang, Lu Li, Xingyu Ji +5

Signed graphs are powerful models for representing complex relations with both positive and negative connections. Recently, Signed Graph Neural Networks (SGNNs) have emerged as pot…

cs.LG2023

Enhancing Student Performance Prediction on Learnersourced Questions with SGNN-LLM Synergy

Lin Ni, Sijie Wang, Zeyu Zhang +4

Learnersourcing offers great potential for scalable education through student content creation. However, predicting student performance on learnersourced questions, which is essent…