6 citations · 10 across the 11 of their papers we have counts for
13 papers
FragFlex: Fragment-Based Flexible Molecular Generation for Exploring Vast Chemical Space
Sihyun Park, David Ryan Koes
Drug discovery requires efficient exploration of an astronomically large chemical space. Molecular graph diffusion models offer a promising approach to this task, but many require…
Test-Time Adaptation with Query-Dependent Residuals for Visual Document Retrieval
Zeliang Li, Xiaofen Xing, Kailing Guo +1
Visual document retrieval (VDR) systems depend on page embeddings computed before deployment, which makes adaptation difficult when encoder parameters or corpus re-encoding are una…
Beyond Similarity through Zero-Token Geometric Graphs for Multi-Hop RAG
Zeliang Li, Xiaofen Xing, Kailing Guo +1
Multi-hop retrieval-augmented generation (RAG) requires evidence that remains relevant to a query while introducing enough novelty to bridge semantic gaps. Dense retrieval tends to…
AhaKV: Adaptive Holistic Attention-Driven KV Cache Eviction for Efficient Inference of Large Language Models
Yifeng Gu, Zicong Jiang, Jianxiu Jin +3
Large Language Models (LLMs) have significantly advanced the field of Artificial Intelligence. However, their deployment is resource-intensive, not only due to the large number of…
Shared Attention-based Autoencoder with Hierarchical Fusion-based Graph Convolution Network for sEEG SOZ Identification
Huachao Yan, Kailing Guo, Shiwei Song +4
Diagnosing seizure onset zone (SOZ) is a challenge in neurosurgery, where stereoelectroencephalography (sEEG) serves as a critical technique. In sEEG SOZ identification, the existi…
Boosting Cross-Domain Point Classification via Distilling Relational Priors from 2D Transformers
Longkun Zou, Wanru Zhu, Ke Chen +4
Semantic pattern of an object point cloud is determined by its topological configuration of local geometries. Learning discriminative representations can be challenging due to larg…
CorrTalk: Correlation Between Hierarchical Speech and Facial Activity Variances for 3D Animation
Zhaojie Chu, Kailing Guo, Xiaofen Xing +3
Speech-driven 3D facial animation is a challenging cross-modal task that has attracted growing research interest. During speaking activities, the mouth displays strong motions, whi…
Dynamic Shuffle: An Efficient Channel Mixture Method
Kaijun Gong, Zhuowen Yin, Yushu Li +2
The redundancy of Convolutional neural networks not only depends on weights but also depends on inputs. Shuffling is an efficient operation for mixing channel information but the s…
LAPP: Layer Adaptive Progressive Pruning for Compressing CNNs from Scratch
Pucheng Zhai, Kailing Guo, Fang Liu +2
Structured pruning is a commonly used convolutional neural network (CNN) compression approach. Pruning rate setting is a fundamental problem in structured pruning. Most existing wo…
Compact Model Training by Low-Rank Projection with Energy Transfer
Kailing Guo, Zhenquan Lin, Canyang Chen +3
Low-rankness plays an important role in traditional machine learning, but is not so popular in deep learning. Most previous low-rank network compression methods compress networks b…
Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values
Zhenquan Lin, Kailing Guo, Xiaofen Xing +1
To obtain good performance, convolutional neural networks are usually over-parameterized. This phenomenon has stimulated two interesting topics: pruning the unimportant weights for…
Deep Sampling Networks
Bolun Cai, Xiangmin Xu, Kailing Guo +2
Deep convolutional neural networks achieve excellent image up-sampling performance. However, CNN-based methods tend to restore high-resolution results highly depending on tradition…
Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network
Xiaoyi Jia, Xiangmin Xu, Bolun Cai +1
Methods based on convolutional neural network (CNN) have demonstrated tremendous improvements on single image super-resolution. However, the previous methods mainly restore images…