no code implementations • EMNLP 2020 • Lijie Wang, Ao Zhang, Kun Wu, Ke Sun, Zhenghua Li, Hua Wu, Min Zhang, Haifeng Wang
This paper describes in detail the construction process and data statistics of DuSQL.
no code implementations • 16 Apr 2024 • Ruifeng Li, Dongzhan Zhou, Ancheng Shen, Ao Zhang, Mao Su, Mingqian Li, Hongyang Chen, Gang Chen, Yin Zhang, Shufei Zhang, Yuqiang Li, Wanli Ouyang
Overall, our work illustrates the benefits and potential of using PEMAL in AIDD and other scenarios with data scarcity and noise.
no code implementations • 7 Jan 2024 • He Wang, Pengcheng Guo, Yue Li, Ao Zhang, Jiayao Sun, Lei Xie, Wei Chen, Pan Zhou, Hui Bu, Xin Xu, BinBin Zhang, Zhuo Chen, Jian Wu, Longbiao Wang, Eng Siong Chng, Sun Li
To promote speech processing and recognition research in driving scenarios, we build on the success of the Intelligent Cockpit Speech Recognition Challenge (ICSRC) held at ISCSLP 2022 and launch the ICASSP 2024 In-Car Multi-Channel Automatic Speech Recognition (ICMC-ASR) Challenge.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
1 code implementation • 27 Dec 2023 • Linglong Qian, Zina Ibrahim, Hugh Logan Ellis, Ao Zhang, Yuezhou Zhang, Tao Wang, Richard Dobson
This study presents a novel approach to addressing the challenge of missing data in multivariate time series, with a particular focus on the complexities of healthcare data.
no code implementations • 15 Dec 2023 • Ao Zhang, Pan Zhou, Kaixun Huang, Yong Zou, Ming Liu, Lei Xie
Open-vocabulary keyword spotting (KWS), which allows users to customize keywords, has attracted increasingly more interest.
1 code implementation • 8 Nov 2023 • Ao Zhang, Yuan YAO, Wei Ji, Zhiyuan Liu, Tat-Seng Chua
The development of large language models (LLMs) has greatly advanced the field of multimodal understanding, leading to the emergence of large multimodal models (LMMs).
no code implementations • 7 Oct 2023 • Kaixun Huang, Ao Zhang, BinBin Zhang, Tianyi Xu, Xingchen Song, Lei Xie
However, unlike shallow fusion methods that directly bias the posterior of the ASR model, deep biasing methods implicitly integrate contextual information, making it challenging to control the degree of bias.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 1 Jun 2023 • Tianyi Xu, Zhanheng Yang, Kaixun Huang, Pengcheng Guo, Ao Zhang, Biao Li, Changru Chen, Chao Li, Lei Xie
By incorporating additional contextual information, deep biasing methods have emerged as a promising solution for speech recognition of personalized words.
no code implementations • 21 May 2023 • Kaixun Huang, Ao Zhang, Zhanheng Yang, Pengcheng Guo, Bingshen Mu, Tianyi Xu, Lei Xie
In this study, we introduce a contextual phrase prediction network for an attention-based deep bias method.
1 code implementation • NeurIPS 2023 • Ao Zhang, Hao Fei, Yuan YAO, Wei Ji, Li Li, Zhiyuan Liu, Tat-Seng Chua
While developing a new multimodal LLM (MLLM) by pre-training on tremendous image-text pairs from scratch can be exceedingly resource-consuming, connecting an existing LLM with a comparatively lightweight visual prompt generator (VPG) becomes a feasible paradigm.
no code implementations • 11 Mar 2023 • Pengcheng Guo, He Wang, Bingshen Mu, Ao Zhang, Peikun Chen
This paper describes our NPU-ASLP system for the Audio-Visual Diarization and Recognition (AVDR) task in the Multi-modal Information based Speech Processing (MISP) 2022 Challenge.
1 code implementation • 22 Nov 2022 • Yuan YAO, Tianyu Yu, Ao Zhang, Mengdi Li, Ruobing Xie, Cornelius Weber, Zhiyuan Liu, Hai-Tao Zheng, Stefan Wermter, Tat-Seng Chua, Maosong Sun
In this work, we present CLEVER, which formulates CKE as a distantly supervised multi-instance learning problem, where models learn to summarize commonsense relations from a bag of images about an entity pair without any human annotation on image instances.
1 code implementation • Findings (ACL) 2022 • Yuan YAO, Bowen Dong, Ao Zhang, Zhengyan Zhang, Ruobing Xie, Zhiyuan Liu, Leyu Lin, Maosong Sun, Jianyong Wang
Recent works have shown promising results of prompt tuning in stimulating pre-trained language models (PLMs) for natural language processing (NLP) tasks.
1 code implementation • 23 May 2022 • Yuan YAO, Qianyu Chen, Ao Zhang, Wei Ji, Zhiyuan Liu, Tat-Seng Chua, Maosong Sun
We show that PEVL enables state-of-the-art performance of detector-free VLP models on position-sensitive tasks such as referring expression comprehension and phrase grounding, and also improves the performance on position-insensitive tasks with grounded inputs.
Ranked #1 on Visual Commonsense Reasoning on VCR (Q-AR) test
2 code implementations • 22 Mar 2022 • Ao Zhang, Yuan YAO, Qianyu Chen, Wei Ji, Zhiyuan Liu, Maosong Sun, Tat-Seng Chua
Scene graph generation (SGG) is designed to extract (subject, predicate, object) triplets in images.
Ranked #1 on Predicate Classification on Visual Genome
1 code implementation • 24 Sep 2021 • Yuan YAO, Ao Zhang, Zhengyan Zhang, Zhiyuan Liu, Tat-Seng Chua, Maosong Sun
Pre-Trained Vision-Language Models (VL-PTMs) have shown promising capabilities in grounding natural language in image data, facilitating a broad variety of cross-modal tasks.
no code implementations • 14 Jun 2021 • Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Yuan YAO, Ao Zhang, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, Jun Zhu
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success and become a milestone in the field of artificial intelligence (AI).
1 code implementation • 2 May 2021 • Ao Zhang, Farzan Erlik Nowruzi, Robert Laganiere
In this paper, we collect a novel radar dataset that contains radar data in the form of Range-Azimuth-Doppler tensors along with the bounding boxes on the tensor for dynamic road users, category labels, and 2D bounding boxes on the Cartesian Bird-Eye-View range map.
1 code implementation • ICCV 2021 • Yuan YAO, Ao Zhang, Xu Han, Mengdi Li, Cornelius Weber, Zhiyuan Liu, Stefan Wermter, Maosong Sun
In this work, we propose visual distant supervision, a novel paradigm of visual relation learning, which can train scene graph models without any human-labeled data.
1 code implementation • EMNLP 2021 • Kun Wu, Lijie Wang, Zhenghua Li, Ao Zhang, Xinyan Xiao, Hua Wu, Min Zhang, Haifeng Wang
For better distribution matching, we require that at least 80% of SQL patterns in the training data are covered by generated queries.
1 code implementation • 16 Jun 2020 • Ao Zhang, Jinwen Ma
Graph neural networks (GNNs) achieve remarkable performance for tasks on graph data.
no code implementations • 15 Jan 2018 • Ao Zhang, Nan Li, Jian Pu, Jun Wang, Junchi Yan, Hongyuan Zha
Learning a classifier with control on the false-positive rate plays a critical role in many machine learning applications.