Papers by Selcuk Sandikci

1 papers
An Empirical Study of Speculative Decoding for Small Language Models (2026.eacl-long)

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Challenge: Existing studies focus on 7B-70B parameters models, leaving a knowledge gap for small language models.
Approach: They propose a draft-then-verify paradigm that allows for a single forward pass through a model and transfer of all model parameters to the GPU cache.
Outcome: The proposed method can be used to accelerate small language models with low computational overhead.

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