3 papers
cs.LG2026
Forget Less, Generalize More: Unifying Temporal and Structural Adaptation for Dynamic Graphs
Qian Chang, Ciprian Doru Giurcaneanu, Runsong Jia +6
Representation learning on dynamic graphs requires capturing complex dependencies that evolve across both time and structure. Existing approaches typically adopt fixed temporal dec…
cs.LG2026
Graph Retention Networks for Dynamic Graphs
Qian Chang, Xia Li, Xiufeng Cheng +4
In this paper, we propose Graph Retention Networks (GRNs) as a unified architecture for deep learning on dynamic graphs. The GRN extends the concept of retention into dynamic graph…
cs.CL2025
Evaluating Large Language Models on Multimodal Chemistry Olympiad Exams
Yiming Cui, Xin Yao, Yuxuan Qin +3
Multimodal scientific reasoning remains a significant challenge for large language models (LLMs), particularly in chemistry, where problem-solving relies on symbolic diagrams, mole…