Papers by Ankur Aggarwal

1 papers
MASSV: Multimodal Adaptation and Self-Data Distillation for Speculative Decoding of Vision-Language Models (2025.findings-emnlp)

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Challenge: Speculative decoding of vision-language models provides a novel way to accelerate language model inference by enabling a lightweight draft model to propose multiple tokens that a larger target model verifies simultaneously.
Approach: They propose a technique that allows a lightweight draft model to propose multiple tokens that a larger target model verifies simultaneously.
Outcome: The proposed technique increases accepted length by 30% and delivers speedups of up to 1.46x compared to conventional text-only drafting baselines on visually-grounded tasks.

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