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20242026
most citedSelf-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models

1 citations · 2 across the 6 of their papers we have counts for

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6 papers

cs.CL2026

Conformal Path Reasoning: Trustworthy Knowledge Graph Question Answering via Path-Level Calibration

Shuhang Lin, Chuhao Zhou, Xiao Lin +5

Knowledge Graph Question Answering (KGQA) offers grounded, interpretable reasoning, but existing methods often fail to provide reliable coverage guarantees over retrieved answers.…

cs.AI2025

Toward Clinically Explainable AI for Medical Diagnosis: A Foundation Model with Human-Compatible Reasoning via Reinforcement Learning

Qika Lin, Yifan Zhu, Bin Pu +14

The clinical adoption of artificial intelligence (AI) in medical diagnostics is critically hampered by its black-box nature, which prevents clinicians from verifying the rationale…

cs.LG2025★ 1 cited

A Survey of Quantized Graph Representation Learning: Connecting Graph Structures with Large Language Models

Qika Lin, Zhen Peng, Kaize Shi +5

Recent years have witnessed rapid advances in graph representation learning, with the continuous embedding approach emerging as the dominant paradigm. However, such methods encount…

cs.CL2025★ 1 cited

Self-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models

Qika Lin, Tianzhe Zhao, Kai He +5

Due to the presence of the natural gap between Knowledge Graph (KG) structures and the natural language, the effective integration of holistic structural information of KGs with La…

cs.AI2024

Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey

Qika Lin, Yifan Zhu, Xin Mei +6

The rapid development of artificial intelligence has constantly reshaped the field of intelligent healthcare and medicine. As a vital technology, multimodal learning has increasing…

cs.LG2024

Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights

Zeqin Yang, Weilin Chen, Ruichu Cai +7

Long-term treatment effect estimation is a significant but challenging problem in many applications. Existing methods rely on ideal assumptions, such as no unobserved confounders o…