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Hangyu Zheng

2 accepted papers

2025

Sparse Learning for State Space Models on Mobile

ICLR 2025poster

Transformer models have been widely investigated in different domains by providing long-range dependency handling and global contextual awareness, driving the development of popular AI applications such as ChatGPT, Gemini, and Alexa. State Space Models (SSMs) have emerged as strong contenders in the…

Cited by 1SourcePDFScholar
2024

Exploring Token Pruning in Vision State Space Models

NeurIPS 2024poster

State Space Models (SSMs) have the advantage of keeping linear computational complexity compared to attention modules in transformers, and have been applied to vision tasks as a new type of powerful vision foundation model. Inspired by the observations that the final prediction in vision transformer…

Cited by 6SourcePDFScholar