most citedLayoutPrompter: Awaken the Design Ability of Large Language Models

6 citations · 16 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG20231 cited

Bridging Data-Driven and Knowledge-Driven Approaches for Safety-Critical Scenario Generation in Automated Vehicle Validation

Kunkun Hao, Lu Liu, Wen Cui +4

Automated driving vehicles~(ADV) promise to enhance driving efficiency and safety, yet they face intricate challenges in safety-critical scenarios. As a result, validating ADV with…

cs.CV20236 cited

LayoutPrompter: Awaken the Design Ability of Large Language Models

Jiawei Lin, Jiaqi Guo, Shizhao Sun +3

Conditional graphic layout generation, which automatically maps user constraints to high-quality layouts, has attracted widespread attention today. Although recent works have achie…

cs.SD20231 cited

U-DiT TTS: U-Diffusion Vision Transformer for Text-to-Speech

Xin Jing, Yi Chang, Zijiang Yang +3

Deep learning has led to considerable advances in text-to-speech synthesis. Most recently, the adoption of Score-based Generative Models (SGMs), also known as Diffusion Probabilist…

cs.SD2023

HEAR4Health: A blueprint for making computer audition a staple of modern healthcare

Andreas Triantafyllopoulos, Alexander Kathan, Alice Baird +20

Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalen…

cs.SD20224 cited

Redundancy Reduction Twins Network: A Training framework for Multi-output Emotion Regression

Xin Jing, Meishu Song, Andreas Triantafyllopoulos +2

In this paper, we propose the Redundancy Reduction Twins Network (RRTN), a redundancy reduction training framework that minimizes redundancy by measuring the cross-correlation matr…

cs.SD20224 cited

Dynamic Restrained Uncertainty Weighting Loss for Multitask Learning of Vocal Expression

Meishu Song, Zijiang Yang, Andreas Triantafyllopoulos +6

We propose a novel Dynamic Restrained Uncertainty Weighting Loss to experimentally handle the problem of balancing the contributions of multiple tasks on the ICML ExVo 2022 Challen…