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cs.LG2026
When Does Task-Aware Imputation Matter? An Analysis of Robustness Under Train-Test Mismatch
Maria V. Salvador, Ana F. Sequeira, Jaime S. Cardoso
Missing data is a pervasive challenge in machine learning, often degrading predictive performance and complicating model deployment. Most existing approaches treat imputation as a…
cs.LG2026
AdaFlash: Adaptive Speculative Decoding via On-Policy Distilled Diffusion Drafters
Yu-Yang Qian, Hao-Cong Wu, Chen Chen +4
Speculative decoding, in which a lightweight draft model first generates a draft sequence that is then verified by the target model, has become a prevalent paradigm for acceleratin…
cs.LG2026
When Drafts Evolve: Speculative Decoding Meets Online Learning
Yu-Yang Qian, Hao-Cong Wu, Yichao Fu +2
Speculative decoding has emerged as a widely adopted paradigm for accelerating large language model inference, where a lightweight draft model rapidly generates candidate tokens th…