83 citations · 86 across the 8 of their papers we have counts for
4 papers · 1 filter
RaBitQCache: Rotated Binary Quantization for KVCache in Long Context LLM Inference
Wenhao Li, Jinhao Dong, Hailin Zhang +3
Long-context Large Language Model inference is severely bottlenecked by the massive Key-Value (KV) cache, yet existing sparse attention methods often suffer from static fixed-budge…
SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling
Xiaodong Ji, Hailin Zhang, Fangcheng Fu +1
Many advanced Large Language Model (LLM) applications require long-context processing, but the self-attention module becomes a bottleneck during the prefilling stage of inference d…
MEMO: Fine-grained Tensor Management For Ultra-long Context LLM Training
Pinxue Zhao, Hailin Zhang, Fangcheng Fu +9
Nowadays, Large Language Models (LLMs) have been trained using extended context lengths to foster more creative applications. However, long context training poses great challenges…
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling
Shuaipeng Li, Penghao Zhao, Hailin Zhang +10
In current deep learning tasks, Adam style optimizers such as Adam, Adagrad, RMSProp, Adafactor, and Lion have been widely used as alternatives to SGD style optimizers. These optim…