activity
20212025
most citedMogaNet: Multi-order Gated Aggregation Network

24 citations · 57 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2025

Life-Code: Central Dogma Modeling with Multi-Omics Sequence Unification

Zicheng Liu, Siyuan Li, Zhiyuan Chen +6

The interactions between DNA, RNA, and proteins are fundamental to biological processes, as illustrated by the central dogma of molecular biology. Although modern biological pre-tr…

quant-ph2024★ 1 cited

Establishing a New Benchmark in Quantum Computational Advantage with 105-qubit Zuchongzhi 3.0 Processor

Dongxin Gao, Daojin Fan, Chen Zha +151

In the relentless pursuit of quantum computational advantage, we present a significant advancement with the development of Zuchongzhi 3.0. This superconducting quantum computer pro…

q-bio.QM2024★ 7 cited

BEACON: Benchmark for Comprehensive RNA Tasks and Language Models

Yuchen Ren, Zhiyuan Chen, Lifeng Qiao +10

RNA plays a pivotal role in translating genetic instructions into functional outcomes, underscoring its importance in biological processes and disease mechanisms. Despite the emerg…

q-bio.BM2023★ 10 cited

Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration

Haitao Lin, Yufei Huang, Odin Zhang +4

In recent years, AI-assisted drug design methods have been proposed to generate molecules given the pockets' structures of target proteins. Most of them are atom-level-based method…

cs.CV2022★ 24 cited

MogaNet: Multi-order Gated Aggregation Network

Siyuan Li, Zedong Wang, Zicheng Liu +6

By contextualizing the kernel as global as possible, Modern ConvNets have shown great potential in computer vision tasks. However, recent progress on multi-order game-theoretic int…

cs.LG2021

GenURL: A General Framework for Unsupervised Representation Learning

Siyuan Li, Zicheng Liu, Zelin Zang +3

Unsupervised representation learning (URL), which learns compact embeddings of high-dimensional data without supervision, has made remarkable progress recently. However, the develo…

cs.CV2021★ 4 cited

AutoMix: Unveiling the Power of Mixup for Stronger Classifiers

Zicheng Liu, Siyuan Li, Di Wu +4

Data mixing augmentation have proved to be effective in improving the generalization ability of deep neural networks. While early methods mix samples by hand-crafted policies (e.g.…

cs.CV2021★ 11 cited

Reformulating HOI Detection as Adaptive Set Prediction

Mingfei Chen, Yue Liao, Si Liu +3

Determining which image regions to concentrate on is critical for Human-Object Interaction (HOI) detection. Conventional HOI detectors focus on either detected human and object pai…