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Home/Authors/Yuan Shen

Yuan Shen

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

AI×2Distributed×2ML×1NLP×1

Frequent co-authors

Akarsh K Nair1×
Muhammad Arifur Rahman1×
Nicholas Shopland1×
Andy Burton1×
Jun He1×
David Baldwin1×

Research Timeline

2026
When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors

This paper systematically evaluates tabular data referencing errors in large language models and presents methods to improve answer accuracy and detect errors.

Every Microsecond Matters: Achieving Near Speed-of-Light Latency in GPU Collectives

This paper explores methods to reduce latency in GPU collective communications for large language model inference, achieving near-optimal designs with barrier-free synchronization and efficient use of symmetric memory and multicast.

SynPre-FL: Synthetic data-driven pretraining integrated Federated Learning training framework

This paper proposes SynPre-FL, a framework that combines high-fidelity synthetic EHR generation with federated learning for robust clinical prediction.

Highlighted terms show continued research focus across papers

Papers

cs.LGcs.AIcs.DCEmpiricalRecentJul 21, 2026

SynPre-FL: Synthetic data-driven pretraining integrated Federated Learning training framework

Akarsh K Nair, Muhammad Arifur Rahman, Nicholas Shopland, Andy Burton +7 more

This paper proposes SynPre-FL, a framework that combines high-fidelity synthetic EHR generation with federated learning for robust clinical prediction.

View →
cs.DCEmpirical
Recent
Jul 17, 2026

Every Microsecond Matters: Achieving Near Speed-of-Light Latency in GPU Collectives

Siyuan Shen, Anton Korzh, John Bachan, Tiancheng Chen +9 more

This paper explores methods to reduce latency in GPU collective communications for large language model inference, achieving near-optimal designs with barrier-free synchronization and efficient use of…

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cs.CLcs.AIEmpiricalRecentJun 30, 2026

When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors

Yuqing Yang, Qi Zhu, Zhen Han, Boran Han +4 more

This paper systematically evaluates tabular data referencing errors in large language models and presents methods to improve answer accuracy and detect errors.

View →