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#machine learning Preprint Sep 2026

Simple Diffusion Language Models Are More Effective Few-Step Generators Than Reported

Diffusion language models (DLMs) promise fast parallel generation, yet high-quality samples often require large number of refinement steps, which diminishes their advantage in practice. This has led to massive interest in and rapid development of new methods for effective few-step generation. We show that much of the s...

H. Amin, Ming Yin, Rajiv Khanna · 0 citations
#human-computer interacti... Preprint Aug 2026

Graphionale: How Graph Visualizations of LLM Rationales Affect Human Decision Making

Graphionale is developed as a testbed for empirically studying argument-map-style rationale visualization, and its findings contribute empirical design knowledge about when and how graphical rationales support human decision making, and inform the next-generation reasoning-aware AI interfaces.

Xin-Ru Wang, Zhexue Ma, Ming Yin et al. · 0 citations

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