no code implementations • 24 Apr 2024 • Kaining Ying, Fanqing Meng, Jin Wang, Zhiqian Li, Han Lin, Yue Yang, Hao Zhang, Wenbo Zhang, Yuqi Lin, Shuo Liu, Jiayi Lei, Quanfeng Lu, Runjian Chen, Peng Xu, Renrui Zhang, Haozhe Zhang, Peng Gao, Yali Wang, Yu Qiao, Ping Luo, Kaipeng Zhang, Wenqi Shao
Large Vision-Language Models (LVLMs) show significant strides in general-purpose multimodal applications such as visual dialogue and embodied navigation.
1 code implementation • 23 Apr 2024 • Zhen Yang, Fang Liu, Zhongxing Yu, Jacky Wai Keung, Jia Li, Shuo Liu, Yifan Hong, Xiaoxue Ma, Zhi Jin, Ge Li
Specifically, UniTrans first craft a series of test cases for target programs with the assistance of source programs.
no code implementations • 19 Apr 2024 • Hongzhi Qi, Hanfei Liu, Jianqiang Li, Qing Zhao, Wei Zhai, Dan Luo, Tian Yu He, Shuo Liu, Bing Xiang Yang, Guanghui Fu
Seven pre-trained models were evaluated in two tasks: high and low suicide risk, and fine-grained suicide risk classification on a level of 0 to 10.
1 code implementation • 17 Apr 2024 • Shuo Liu, Junhao Shen, Hong Qian, Aimin Zhou
To this end, this paper proposes an inductive cognitive diagnosis model (ICDM) for fast new students' mastery levels inference in WOIESs.
no code implementations • 30 Oct 2023 • Shuo Liu, Gail Kaiser
Vulnerability identification is crucial to protect software systems from attacks for cyber-security.
1 code implementation • 7 Sep 2023 • Hongzhi Qi, Qing Zhao, Changwei Song, Wei Zhai, Dan Luo, Shuo Liu, Yi Jing Yu, Fan Wang, Huijing Zou, Bing Xiang Yang, Jianqiang Li, Guanghui Fu
In response, we introduce two novel annotated datasets from Chinese social media, focused on cognitive distortions and suicidal risk classification.
1 code implementation • 6 Sep 2023 • Shuo Liu, Lulu Han, Xiaoyang Liu, Junli Ren, Fang Wang, YingLiu, Yuanshan Lin
Wherein, a basic module performs target association based on IoU of detection boxes between successive frames to deal with morphological change of fish; an interaction module combines IoU of detection boxes and IoU of fish entity to handle occlusions; a refind module use spatio-temporal information uses spatio-temporal information to overcome the tracking failure resulting from the missed detection by the detector under complex environment.
1 code implementation • 29 Aug 2023 • Guanghui Fu, Qing Zhao, Jianqiang Li, Dan Luo, Changwei Song, Wei Zhai, Shuo Liu, Fan Wang, Yan Wang, Lijuan Cheng, Juan Zhang, Bing Xiang Yang
In the contemporary landscape of social media, an alarming number of users express negative emotions, some of which manifest as strong suicidal intentions.
no code implementations • 19 Aug 2023 • Jean-Michel Benkert, Igor Letina, Shuo Liu
We study how competitive forces may drive firms to inefficiently acquire startup talent.
no code implementations • 29 Jul 2023 • Richard W. Longman, Shuo Liu, Tarek A. Elsharhawy
Iterative Learning Control (ILC) records previous run tracking error, adjusts the next run command, aiming for zero tracking error in the real world, not our model of the world.
1 code implementation • 15 Jun 2023 • Peng Xu, Wenqi Shao, Kaipeng Zhang, Peng Gao, Shuo Liu, Meng Lei, Fanqing Meng, Siyuan Huang, Yu Qiao, Ping Luo
Large Vision-Language Models (LVLMs) have recently played a dominant role in multimodal vision-language learning.
no code implementations • 14 Jun 2023 • Zhiqiang Que, Shuo Liu, Markus Rognlien, Ce Guo, Jose G. F. Coutinho, Wayne Luk
This paper introduces a novel optimization framework for deep neural network (DNN) hardware accelerators, enabling the rapid development of customized and automated design flows.
no code implementations • 30 May 2023 • Shuo Liu, Leda Sari, Chunyang Wu, Gil Keren, Yuan Shangguan, Jay Mahadeokar, Ozlem Kalinli
This paper presents a method for selecting appropriate synthetic speech samples from a given large text-to-speech (TTS) dataset as supplementary training data for an automatic speech recognition (ASR) model.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 16 Nov 2022 • Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
In particular, we introduce the notion of $(f, r; \epsilon)$-resilience to characterize how well the true solution is approximated in the presence of up to $f$ Byzantine faulty agents, and up to $r$ slow agents (or stragglers) -- smaller $\epsilon$ represents a better approximation.
1 code implementation • 7 Nov 2022 • Yi Zhai, Yu Zhang, Shuo Liu, Xiaomeng Chu, Jie Peng, Jianmin Ji, Yanyong Zhang
Instead of extracting features from the tensor program itself, TLP extracts features from the schedule primitives.
no code implementations • 6 Oct 2022 • Andreas Triantafyllopoulos, Björn W. Schuller, Gökçe İymen, Metin Sezgin, Xiangheng He, Zijiang Yang, Panagiotis Tzirakis, Shuo Liu, Silvan Mertes, Elisabeth André, Ruibo Fu, JianHua Tao
Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research.
no code implementations • 27 Jul 2022 • Jianshu Li, Man Luo, Jian Liu, Tao Chen, Chengjie Wang, Ziwei Liu, Shuo Liu, Kewei Yang, Xuning Shao, Kang Chen, Boyuan Liu, Mingyu Guo, Ying Guo, Yingying Ao, Pengfei Gao
In this paper, we present the solutions from the Top 3 teams, in order to boost the research work in the field of image forgery detection.
1 code implementation • Nature Machine Intelligence 2022 • Yuquan Li, Chang-Yu Hsieh, Ruiqiang Lu, Xiaoqing Gong, Xiaorui Wang, Pengyong Li, Shuo Liu, Yanan Tian, Dejun Jiang, Jiaxian Yan, Qifeng Bai, Huanxiang Liu, Shengyu Zhang, Xiaojun Yao
In fact, the pursuit of high prediction performance on a limited number of datasets has crystallized their architectures and hyperparameters, making them lose advantage in repurposing to new data generated in drug discovery.
Ranked #1 on Drug Discovery on ToxCast (Toxicity Forecaster)
no code implementations • 31 Mar 2022 • Xin Jing, Shuo Liu, Emilia Parada-Cabaleiro, Andreas Triantafyllopoulos, Meishu Song, Zijiang Yang, Björn W. Schuller
Detecting COVID-19 from audio signals, such as breathing and coughing, can be used as a fast and efficient pre-testing method to reduce the virus transmission.
no code implementations • 2 Mar 2022 • Shuo Liu, Adria Mallol-Ragolta, Emilia Parada-Cabeleiro, Kun Qian, Xin Jing, Alexander Kathan, Bin Hu, Bjoern W. Schuller
Inspired by the humans' cognitive ability to generalise knowledge and skills, Self-Supervised Learning (SSL) targets at discovering general representations from large-scale data without requiring human annotations, which is an expensive and time consuming task.
no code implementations • 22 Dec 2021 • Shaoxiong Sun, Amos A Folarin, Yuezhou Zhang, NIcholas Cummins, Shuo Liu, Callum Stewart, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Petroula Laiou, Heet Sankesara, Gloria Dalla Costa, Letizia Leocani, Per Soelberg Sørensen, Melinda Magyari, Ana Isabel Guerrero, Ana Zabalza, Srinivasan Vairavan, Raquel Bailon, Sara Simblett, Inez Myin-Germeys, Aki Rintala, Til Wykes, Vaibhav A Narayan, Matthew Hotopf, Giancarlo Comi, Richard JB Dobson, RADAR-CNS consortium
In this work, we extracted 96 activity features in different temporal granularities (from minute-level to day-level) and explored their utility in estimating 6MWT scores in a European (Italy, Spain, and Denmark) MS cohort of 337 participants over an average of 10-month duration.
no code implementations • 21 Oct 2021 • Shuo Liu, Nirupam Gupta, Nitin Vaidya
We demonstrate, both theoretically and empirically, the merits of our proposed redundancy model in improving the robustness of DGD against asynchronous and Byzantine agents, and their extensions to distributed stochastic gradient descent (D-SGD) for robust distributed machine learning with asynchronous and Byzantine agents.
no code implementations • 14 Oct 2021 • Yufeng Wang, Yi-Hsuan Tsai, Wei-Chih Hung, Wenrui Ding, Shuo Liu, Ming-Hsuan Yang
Multi-Task Learning (MTL) aims to enhance the model generalization by sharing representations between related tasks for better performance.
no code implementations • 13 Oct 2021 • Andreas Triantafyllopoulos, Uwe Reichel, Shuo Liu, Stephan Huber, Florian Eyben, Björn W. Schuller
In this contribution, we investigate the effectiveness of deep fusion of text and audio features for categorical and dimensional speech emotion recognition (SER).
no code implementations • 6 Oct 2021 • Shuo Liu, Richard W. Longman
The purpose of this paper is to create a method of designing ILC compensators based on steady state frequency response, and have the ILC converge to zero error in spite of transients and bandwidth.
no code implementations • 6 Oct 2021 • Shuo Liu, Richard W. Longman, Benjamas Panomruttanarug
Iterative Learning Control (ILC) is useful in spacecraft application for repeated high precision scanning maneuvers.
no code implementations • 19 Apr 2021 • Shuo Liu, Jing Han, Estela Laporta Puyal, Spyridon Kontaxis, Shaoxiong Sun, Patrick Locatelli, Judith Dineley, Florian B. Pokorny, Gloria Dalla Costa, Letizia Leocan, Ana Isabel Guerrero, Carlos Nos, Ana Zabalza, Per Soelberg Sørensen, Mathias Buron, Melinda Magyari, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Callum Stewart, Amos A Folarin, Richard JB Dobson, Raquel Bailón, Srinivasan Vairavan, NIcholas Cummins, Vaibhav A Narayan, Matthew Hotopf, Giancarlo Comi, Björn Schuller
This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data.
no code implementations • 11 Aug 2020 • Nirupam Gupta, Shuo Liu, Nitin H. Vaidya
We show that the CGE gradient-filter guarantees fault-tolerance against a bounded fraction of Byzantine agents under standard stochastic assumptions, and is computationally simpler compared to many existing gradient-filters such as multi-KRUM, geometric median-of-means, and the spectral filters.
no code implementations • 30 Apr 2020 • Jing Han, Kun Qian, Meishu Song, Zijiang Yang, Zhao Ren, Shuo Liu, Juan Liu, Huaiyuan Zheng, Wei Ji, Tomoya Koike, Xiao Li, Zixing Zhang, Yoshiharu Yamamoto, Björn W. Schuller
In particular, by analysing speech recordings from these patients, we construct audio-only-based models to automatically categorise the health state of patients from four aspects, including the severity of illness, sleep quality, fatigue, and anxiety.
1 code implementation • 16 Nov 2019 • Shuo Liu, Gil Keren, Björn Schuller
N-HANS is a Python toolkit for in-the-wild audio enhancement, including speech, music, and general audio denoising, separation, and selective noise or source suppression.
Sound Audio and Speech Processing
no code implementations • 10 Jul 2019 • Fabien Ringeval, Björn Schuller, Michel Valstar, NIcholas Cummins, Roddy Cowie, Leili Tavabi, Maximilian Schmitt, Sina Alisamir, Shahin Amiriparian, Eva-Maria Messner, Siyang Song, Shuo Liu, Ziping Zhao, Adria Mallol-Ragolta, Zhao Ren, Mohammad Soleymani, Maja Pantic
The Audio/Visual Emotion Challenge and Workshop (AVEC 2019) "State-of-Mind, Detecting Depression with AI, and Cross-cultural Affect Recognition" is the ninth competition event aimed at the comparison of multimedia processing and machine learning methods for automatic audiovisual health and emotion analysis, with all participants competing strictly under the same conditions.
no code implementations • 24 Jun 2019 • Shuo Liu, Gil Keren, Björn Schuller
We present a novel source separation model to decompose asingle-channel speech signal into two speech segments belonging to two different speakers.
no code implementations • 25 Jun 2018 • Shuo Liu, Vijay John, Erik Blasch, Zheng Liu, Ying Huang
Context enhancement is critical for night vision (NV) applications, especially for the dark night situation without any artificial lights.
no code implementations • 31 May 2018 • Yuchen Yang, Shuo Liu, Wei Ma, Qiuyuan Wang, Zheng Liu
The paper presents a Traffic Sign Recognition (TSR) system, which can fast and accurately recognize traffic signs of different sizes in images.
no code implementations • 30 Nov 2017 • Shuo Liu, Zheng Liu
In this study, we propose a novel detection algorithm for military objects by fusing multi-channel CNNs.