1 citations · 3 across the 5 of their papers we have counts for
6 papers
LiveServe: Interaction-Aware Serving for Real-Time Omni-Modal LLMs
Xiangyu Zhi, Peiqi Yin, Sheng Guan +3
Realtime omni-modal LMs support speech-centric conversations where users stream inputs, hear generated audio, and interrupt freely. Existing Omni-LM serving systems still rely on t…
Text-attributed Graph Condensation via Text Selection and Attribute Matching
Haowei Han, Yuxiang Wang, Guojia Wan +5
Text-Attributed Graph (TAG) is an important type of graph structured data, where each node has a text description. TAG models usually train a Graph Neural Network (GNN) and languag…
SAQ: Pushing the Limits of Vector Quantization through Code Adjustment and Dimension Segmentation
Hui Li, Shiyuan Deng, Xiao Yan +2
Approximate Nearest Neighbor Search (ANNS) plays a critical role in applications such as search engines, recommender systems, and RAG for LLMs. Vector quantization (VQ), a crucial…
PilotANN: Memory-Bounded GPU Acceleration for Vector Search
Yuntao Gui, Peiqi Yin, Xiao Yan +3
Approximate Nearest Neighbor Search (ANNS) has become fundamental to modern deep learning applications, having gained particular prominence through its integration into recent gene…
SPT: Fine-Tuning Transformer-based Language Models Efficiently with Sparsification
Yuntao Gui, Xiao Yan, Peiqi Yin +2
Transformer-based large language models (e.g., BERT and GPT) achieve great success, and fine-tuning, which tunes a pre-trained model on a task-specific dataset, is the standard pra…
Elastic deep learning in multi-tenant GPU cluster
Yidi Wu, Kaihao Ma, Xiao Yan +6
We study how to support elasticity, i.e., the ability to dynamically adjust the parallelism (number of GPUs), for deep neural network (DNN) training. Elasticity can benefit multi-t…