most citedHolistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning

51 citations

8 papers

q-bio.BM2022★ 9 cited

Accelerating Antimicrobial Peptide Discovery with Latent Structure

Danqing Wang, Zeyu Wen, Fei Ye +2

Antimicrobial peptides (AMPs) are promising therapeutic approaches against drug-resistant pathogens. Recently, deep generative models are used to discover new AMPs. However, previo…

eess.AS2022★ 4 cited

Ontology-aware Learning and Evaluation for Audio Tagging

Haohe Liu, Qiuqiang Kong, Xubo Liu +3

This study defines a new evaluation metric for audio tagging tasks to overcome the limitation of the conventional mean average precision (mAP) metric, which treats different kinds…

quant-ph2022★ 1 cited

Orbital Expansion Variational Quantum Eigensolver: Enabling Efficient Simulation of Molecules with Shallow Quantum Circuit

Yusen Wu, Zigeng Huang, Jinzhao Sun +3

In the noisy-intermediate-scale-quantum era, Variational Quantum Eigensolver (VQE) is a promising method to study ground state properties in quantum chemistry, materials science, a…

cs.CL2022★ 25 cited

Personalized Dialogue Generation with Persona-Adaptive Attention

Qiushi Huang, Yu Zhang, Tom Ko +4

Persona-based dialogue systems aim to generate consistent responses based on historical context and predefined persona. Unlike conventional dialogue generation, the persona-based d…

cs.CV2022★ 51 cited

Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning

Nan Xue, Tianfu Wu, Song Bai +4

This article presents Holistically-Attracted Wireframe Parsing (HAWP), a method for geometric analysis of 2D images containing wireframes formed by line segments and junctions. HAW…

cs.NI2022★ 12 cited

Linker Code Size Optimization for Native Mobile Applications

Gai Liu, Umar Farooq, Chengyan Zhao +2

Modern mobile applications have grown rapidly in binary size, which restricts user growth and hinders updates for existing users. Thus, reducing the binary size is important for ap…