activity
20062024
most citedThe DArk Matter Particle Explorer mission

322 citations · 1k across the 47 of their papers we have counts for

collaborators

49 papers

cs.CV2024★ 6 cited

Superpixelwise Low-rank Approximation based Partial Label Learning for Hyperspectral Image Classification

Shujun Yang, Yu Zhang, Yao Ding +1

Insufficient prior knowledge of a captured hyperspectral image (HSI) scene may lead the experts or the automatic labeling systems to offer incorrect labels or ambiguous labels (i.e…

cs.NI2023★ 13 cited

LLMCad: Fast and Scalable On-device Large Language Model Inference

Daliang Xu, Wangsong Yin, Xin Jin +4

Generative tasks, such as text generation and question answering, hold a crucial position in the realm of mobile applications. Due to their sensitivity to privacy concerns, there i…

cs.CV2023

SSPFusion: A Semantic Structure-Preserving Approach for Infrared and Visible Image Fusion

Qiao Yang, Yu Zhang, Yutong Chen +2

Most existing learning-based multi-modality image fusion (MMIF) methods suffer from significant structure inconsistency due to their inappropriate usage of structural features at t…

cs.CV2023★ 1 cited

UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory

Haiwen Diao, Bo Wan, Ying Zhang +3

Parameter-efficient transfer learning (PETL), i.e., fine-tuning a small portion of parameters, is an effective strategy for adapting pre-trained models to downstream domains. To fu…

cs.DB2023★ 1 cited

DSPC: Efficiently Answering Shortest Path Counting on Dynamic Graphs

Qingshuai Feng, You Peng, Wenjie Zhang +2

The widespread use of graph data in various applications and the highly dynamic nature of today's networks have made it imperative to analyze structural trends in dynamic graphs on…

cs.CV2023★ 45 cited

Plug-and-Play Regulators for Image-Text Matching

Haiwen Diao, Ying Zhang, Wei Liu +2

Exploiting fine-grained correspondence and visual-semantic alignments has shown great potential in image-text matching. Generally, recent approaches first employ a cross-modal atte…