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cs.AR2026
Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction
Vishesh Tripathi, Abhay Kumar, Ramsha Khan
The KV cache is a primary bottleneck for Transformer decoding: its memory footprint and cache-read traffic grow with sequence length. Grouped-query attention (GQA) reduces this cos…
cs.LG2026
Train Smarter, Not Longer: Memorization-Guided Data Reuse for Efficient LLM Training
Jingwei Zuo, Cong Zeng, Ilyas Chahed +6
The training paradigm of large language models has shifted from traditional one-pass training to multi-epoch training, as reasonable reuse of limited high-quality data can improve…
cs.LG2026
Grouped Query Experts: Mixture-of-Experts on GQA Self-Attention
Vishesh Tripathi, Abhay Kumar
Self-attention is central to Transformer performance and is often the most expensive part of the Transformer at long context lengths because its pairwise token interactions scale q…