1 citations · 1 across the 7 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.LG2026
Curriculum Sampling: A Two-Phase Curriculum for Efficient Training of Flow Matching
Pengwei Sun
Timestep sampling is a central design choice in Flow Matching models, yet common practice increasingly favors static middle-biased distributions (e.g., Logit-Normal). We sho…
cs.DC2026
PromptTuner: SLO-Aware Elastic System for LLM Prompt Tuning
Wei Gao, Peng Sun, Dmitrii Ustiugov +2
Prompt tuning has become a prominent strategy for enhancing the performance of Large Language Models (LLMs) on downstream tasks. Many IT enterprises now offer Prompt-Tuning-as-a-Se…
cs.DC2026
CONCUR: High-Throughput Agentic Batch Inference of LLM via Congestion-Based Concurrency Control
Qiaoling Chen, Zhisheng Ye, Tian Tang +7
Batch inference for agentic workloads stresses the GPU key-value (KV) cache in a sustained and cumulative manner, often causing severe throughput degradation well before memory cap…