This work introduces SPECIFICITY PADDING that simply asks the model to copy a few random IDs from the prompt, and that alone makes a title-only request look more human than one that supplies the article's key ideas.
H. Amin, Zhuo-Ran Lu, Ming Yin
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Chun-Wei Chiang, Ming Yin, Harry Yizhou Tian
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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
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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.
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