1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.DC2025
KV Cache Compression for Inference Efficiency in LLMs: A Review
Yanyu Liu, Jingying Fu, Sixiang Liu +4
Withtherapid advancement of large language models (LLMs), the context length for inference has been continuously increasing, leading to an exponential growth in the demand for Key-…
cs.DC2020★ 1 cited
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline
Richard Liaw, Romil Bhardwaj, Lisa Dunlap +4
Prior research in resource scheduling for machine learning training workloads has largely focused on minimizing job completion times. Commonly, these model training workloads colle…
cs.LG2019★ 1 cited
Hierarchical Variational Imitation Learning of Control Programs
Roy Fox, Richard Shin, William Paul +5
Autonomous agents can learn by imitating teacher demonstrations of the intended behavior. Hierarchical control policies are ubiquitously useful for such learning, having the potent…