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Bin Jia

2 accepted papers

2026

OmniScale: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo

AAAI 2026technical

Recent advances in large language models (LLMs) have driven impressive progress in omni-modal understanding and generation. However, training omni-modal LLMs remains a significant challenge due to the heterogeneous model architectures required to process diverse modalities, necessitating sophisticat

Cited by 0SourcePDFScholar
2024

AutoChunk: Automated Activation Chunk for Memory-Efficient Deep Learning Inference

ICLR 2024poster

Large deep learning models have achieved impressive performance across a range of applications. However, their large memory requirements, including parameter memory and activation memory, have become a significant challenge for their practical serving. While existing methods mainly address parameter…

Cited by 0SourcePDFScholar