Papers by Bradley McDanel

    2 papers
    PipeSpec: Breaking Stage Dependencies in Hierarchical LLM Decoding (2025.findings-acl)

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    Challenge: Speculative decoding is limited by sequential stage dependencies that prevent full hardware utilization.
    Approach: They propose a framework that generalizes speculative decoding to use multiple models arranged in a hierarchical pipeline and enables asynchronous execution with lightweight coordination for prediction verification and rollback.
    Outcome: The proposed framework achieves 2.25 tokens/unit through pipelined parallelism with multiple models arranged in a hierarchical pipeline.
    Mitigating Sequential Dependencies: A Survey of Algorithms and Systems for Generation-Refinement Frameworks in Autoregressive Models (2025.findings-emnlp)

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    Challenge: Sequential dependencies present a fundamental bottleneck in deploying large-scale autoregressive models .
    Approach: They analyze methods based on generation strategies and refinement mechanisms . they examine deployment strategies across computing environments and explore applications spanning text, images, and speech generation.
    Outcome: The proposed frameworks can be used to improve the quality of autoregressive models.

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