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Research questionWhen does changing the entropy in attention produce a genuinely different weighting profile rather than merely rescale temperature?Entropy choices can change whether attention has full or truncated support and whether weights decay algebraically or exponentially. Other choices may preserve the weighting shape while changing only the effective temperature, making genuinely new operators difficult to distinguish from rescalings.
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Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.Entropy-Generated Attention Beyond Softmax and Entmax: Kaniadakis and Reciprocal-Symmetric Abe OperatorsThe source analytically derives Kaniadakis and reciprocal-symmetric Abe attention operators and relates them to Softmax, entmax, Rényi, and Sharma–Mittal forms. It establishes full-support algebraic behavior for Kaniadakis attention, symmetry-based expansions for Abe attention, and input-dependent effective temperatures for Rényi and Sharma–Mittal cases; the evidence is theoretical rather than downstream task evaluation.research paper · Sep 3, 2026
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