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Found 3 papers, 1 papers with code
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping
In this work, we observed the saturation of computationally expensive feed-forward blocks of LLM layers and proposed FFN-SkipLLM, which is a novel fine-grained skip strategy of autoregressive LLMs.
MOSEL: Inference Serving Using Dynamic Modality Selection
Rapid advancements over the years have helped machine learning models reach previously hard-to-achieve goals, sometimes even exceeding human capabilities.
ALTIS: Modernizing GPGPU Benchmarking
This paper presents Altis, a benchmark suite for modern GPGPU computing.
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