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Liangyu Zhao

2 accepted papers

2026

Tactic: Adaptive Sparse Attention with Clustering and Distribution Fitting for Long-Context LLMs

ICLR 2026poster

Long-context models are essential for many applications but face inefficiencies in loading large KV caches during decoding. Prior methods enforce fixed token budgets for sparse attention, assuming a set number of tokens can approximate full attention. However, these methods overlook variations in th…

Cited by 0SourceScholar
2021

AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly

ICLR 2021poster

The learning rate (LR) schedule is one of the most important hyper-parameters needing careful tuning in training DNNs. However, it is also one of the least automated parts of machine learning systems and usually costs significant manual effort and computing. Though there are pre-defined LR schedules…