3 papers
cs.LG2026
Latent Block-Diffusion Temporal Point Processes: A Semi-Autoregressive Framework for Asynchronous Event Sequence Generation
Shuai Zhang, Yancheng Chen, Chuan Zhou +5
Modeling and sampling from the underlying distribution of asynchronous event sequences are crucial in various real-world applications, including social networks, medical diagnosis,…
cs.LG2026
Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective
Yancheng Chen, Dun Ma, Shuai Zhang +6
Graph Foundation Models (GFMs), built upon the Pre-training and Adaptation paradigm, have emerged as a research hotspot in graph learning. For GNN-based GFMs, graph prompt tuning h…
cs.AI2026
Hard Constraints Meet Soft Generation: Guaranteed Feasibility for LLM-based Combinatorial Optimization
Yang Liu, Chuan Zhou, Yancheng Chen +3
Large language models (LLMs) have emerged as promising general-purpose solvers for combinatorial optimization (CO), yet they fundamentally lack mechanisms to guarantee solution fea…