6 accepted papers
Large Language Models (LLMs) exhibit pronounced memory-bound characteristics during inference due to High Bandwidth Memory (HBM) bandwidth constraints. In this paper, we propose an L2 Cache-oriented asynchronous KV Cache prefetching method to break through the memory bandwidth bottleneck in LLM infe
Incomplete Multi-View Clustering (IMVC) aims to explore comprehensive representations from multiple views with missing samples. Recent studies have revealed that IMVC methods benefit from Graph Convolutional Network (GCN) in achieving robust feature imputation and effective representation learning.
Existing multi-view clustering methods employ various strategies to address data-level sparsity and view-level dynamic fusion. However, we identify a critical yet overlooked issue: varying sparsity across views. Cross-view sparsity variations lead to encoding discrepancies, heightening sample-level…
Spatial transcriptomics, comprising spatial location and high-throughput gene expression information, provides revolutionary insights into disease discovery and cellular evolution. Spatial transcriptomic clustering, which pinpoints distinct spatial domains within tissues, reveals cellular interactio
Pre-training a model and then fine-tuning it on downstream tasks has demonstrated significant success in the 2D image and NLP domains. However due to the unordered and non-uniform density characteristics of point clouds it is non-trivial to explore the prior knowledge of point clouds and pre-train a…
With the rapid development of various data acquisition technologies, more and more multimodal data come into being. It is important to integrate different modalities which are with high-dimensional features for boosting final multimodal data classification task. However, existing multimodal classifi…