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News/Letting Trajectories Spread: Quality-Preserving Control for Diverse Flow Matching
arxiv
PublishedMay 22, 2026 at 4:00 AM
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Letting Trajectories Spread: Quality-Preserving Control for Diverse Flow Matching

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arXiv:2510.09060v2 Announce Type: replace Abstract: Flow-based text-to-image models follow deterministic trajectories, making it costly to explore diverse modes under limited sampling budgets. Existing approaches to improving diversity often rely on retraining or degrade image fidelity. To address t

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arxivMAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation2harxivCounterfactual Model Testing Under Distribution Shift2harxivCentralized Critics for N-Agent Ad Hoc Teamwork2harxivWhere and What to Reward? Understanding Generalization Between Verifiable and Open-Ended Domains in Reinforcement Learning2h
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