4 papers
S2-Attention: Hardware-Aware Context Sharding Among Attention Heads
Xihui Lin, Yunan Zhang, Suyu Ge +5
Sparse attention, which selectively attends to a subset of tokens in the context was supposed to be efficient. However, its theoretical reduction in FLOPs has rarely translated int…
A Little Goes a Long Way: Efficient Long Context Training and Inference with Partial Contexts
Suyu Ge, Xihui Lin, Yunan Zhang +2
Training and serving long-context large language models (LLMs) incurs substantial overhead. To address this, two critical steps are often required: a pretrained LLM typically under…
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
Suyu Ge, Yunan Zhang, Liyuan Liu +3
In this study, we introduce adaptive KV cache compression, a plug-and-play method that reduces the memory footprint of generative inference for Large Language Models (LLMs). Differ…
GenSERP: Large Language Models for Whole Page Presentation
Zhenning Zhang, Yunan Zhang, Suyu Ge +4
The advent of large language models (LLMs) brings an opportunity to minimize the effort in search engine result page (SERP) organization. In this paper, we propose GenSERP, a frame…