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cs.LG2026
Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle
Xu Bai, Bin Lu, Kun Zhang +4
Graph coarsening is a graph dimensionality reduction technique that aims to construct a smaller and more tractable graph while preserving the essential structural and semantic prop…
cs.LG2026
LEAP: Unlocking dLLM Parallelism via Lookahead Early-Convergence Token Detection
Haohui Zhang, Zhiye Wang, Xiaoying Gan +2
Diffusion Language Models (dLLMs) have garnered significant attention for their potential in highly parallel processing. The parallel capabilities of existing dLLMs stem from the a…