4 papers · 1 filter
SPLA: Block Sparse Plus Linear Attention for Long Context Modeling
Bailin Wang, Dan Friedman, Tao Lei +1
Block-wise sparse attention offers significant efficiency gains for long-context modeling, yet existing methods often suffer from low selection fidelity and cumulative contextual l…
Synthetic bootstrapped pretraining
Zitong Yang, Aonan Zhang, Hong Liu +4
We introduce Synthetic Bootstrapped Pretraining (SBP), a language model (LM) pretraining procedure that first learns a model of relations between documents from the pretraining dat…
CommVQ: Commutative Vector Quantization for KV Cache Compression
Junyan Li, Yang Zhang, Muhammad Yusuf Hassan +8
Large Language Models (LLMs) are increasingly used in applications requiring long context lengths, but the key-value (KV) cache often becomes a memory bottleneck on GPUs as context…
RATTENTION: Towards the Minimal Sliding Window Size in Local-Global Attention Models
Bailin Wang, Chang Lan, Chong Wang +1
Local-global attention models have recently emerged as compelling alternatives to standard Transformers, promising improvements in both training and inference efficiency. However,…