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Showing papers from Soochow University, China Show all papers

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NeurIPS 2026SoochowBaiduTencentBaidu Inc.Soochow University, ChinaEfficient attention & state-space models

Prism Attention: Proposal-Refined Index Sharing Mechanism for Efficient LLMs Inference

Zhenxu Tian, Kebin Liu, Zhengwu Yang, Yi Su and 7 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Soochow universitySoochow University, ChinaSoochowFairness & bias

Malicious Node Injection: A Transferable Adversarial Attack on GNN Fairness

Haotian Zhang, He Huang, Shuang Cui, Yu-e Sun

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SoochowBaiduSoochow University, ChinaHarbin Institute of TechnologyEfficient attention & state-space models

Flux Attention: Context-Aware Hybrid Attention for Efficient LLMs Inference

Flux Attention dynamically routes layer-level attention between full and sparse modes via a lightweight router to accelerate LLM inference, achieving up to 2.8x prefill and 2.0x decode speedups with minimal training.

Quantong Qiu, Zhiyi Hong, Yi Yang, Haitian Wang and 4 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 10 of 20 reviewers recommend it
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