no code implementations • Findings (ACL) 2022 • Amir Pouran Ben Veyseh, Ning Xu, Quan Tran, Varun Manjunatha, Franck Dernoncourt, Thien Nguyen
Toxic span detection is the task of recognizing offensive spans in a text snippet.
no code implementations • NAACL 2022 • Puneet Mathur, Vlad Morariu, Verena Kaynig-Fittkau, Jiuxiang Gu, Franck Dernoncourt, Quan Tran, Ani Nenkova, Dinesh Manocha, Rajiv Jain
We introduce DocTime - a novel temporal dependency graph (TDG) parser that takes as input a text document and produces a temporal dependency graph.
no code implementations • Findings (NAACL) 2022 • Adyasha Maharana, Quan Tran, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Mohit Bansal
We construct and present a new multimodal dataset consisting of software instructional livestreams and containing manual annotations for both detailed and abstract procedural intent that enable training and evaluation of joint video and text understanding models.
no code implementations • 23 Feb 2024 • Hyunjae Kim, Seunghyun Yoon, Trung Bui, Handong Zhao, Quan Tran, Franck Dernoncourt, Jaewoo Kang
Contrastive language-image pre-training (CLIP) models have demonstrated considerable success across various vision-language tasks, such as text-to-image retrieval, where the model is required to effectively process natural language input to produce an accurate visual output.
no code implementations • 30 Nov 2023 • Linzi Xing, Quan Tran, Fabian Caba, Franck Dernoncourt, Seunghyun Yoon, Zhaowen Wang, Trung Bui, Giuseppe Carenini
Video topic segmentation unveils the coarse-grained semantic structure underlying videos and is essential for other video understanding tasks.
no code implementations • 24 Jul 2023 • Viet Dac Lai, Abel Salinas, Hao Tan, Trung Bui, Quan Tran, Seunghyun Yoon, Hanieh Deilamsalehy, Franck Dernoncourt, Thien Huu Nguyen
Punctuation restoration is an important task in automatic speech recognition (ASR) which aim to restore the syntactic structure of generated ASR texts to improve readability.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
1 code implementation • 26 Apr 2023 • Anh Bui, Trung Le, He Zhao, Quan Tran, Paul Montague, Dinh Phung
The key factor for the success of adversarial training is the capability to generate qualified and divergent adversarial examples which satisfy some objectives/goals (e. g., finding adversarial examples that maximize the model losses for simultaneously attacking multiple models).
no code implementations • IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023 • Puneet Mathur, Rajiv Jain, Ashutosh Mehra, Jiuxiang Gu, Franck Dernoncourt, Anandhavelu N, Quan Tran, Verena Kaynig-Fittkau, Ani Nenkova, Dinesh Manocha, Vlad I. Morariu
Experiments show that our approach outperforms competitive baselines by 10-15% on three diverse datasets of forms and mobile app screen layouts for the tasks of spatial region classification, higher-order group identification, layout hierarchy extraction, reading order detection, and word grouping.
1 code implementation • ICLR 2022 • Tuan Anh Bui, Trung Le, Quan Tran, He Zhao, Dinh Phung
We introduce a new Wasserstein cost function and a new series of risk functions, with which we show that standard AT methods are special cases of their counterparts in our framework.
1 code implementation • ICCV 2021 • Zhuowan Li, Elias Stengel-Eskin, Yixiao Zhang, Cihang Xie, Quan Tran, Benjamin Van Durme, Alan Yuille
Our experiments show CCO substantially boosts the performance of neural symbolic methods on real images.
no code implementations • CVPR 2021 • Khoi Pham, Kushal Kafle, Zhe Lin, Zhihong Ding, Scott Cohen, Quan Tran, Abhinav Shrivastava
In this paper, we introduce a large-scale in-the-wild visual attribute prediction dataset consisting of over 927K attribute annotations for over 260K object instances.
no code implementations • COLING 2020 • Quan Tran, Nhan Dam, Tuan Lai, Franck Dernoncourt, Trung Le, Nham Le, Dinh Phung
Interpretability and explainability of deep neural networks are challenging due to their scale, complexity, and the agreeable notions on which the explaining process rests.
1 code implementation • ECCV 2020 • Xihui Liu, Zhe Lin, Jianming Zhang, Handong Zhao, Quan Tran, Xiaogang Wang, Hongsheng Li
We propose a novel algorithm, named Open-Edit, which is the first attempt on open-domain image manipulation with open-vocabulary instructions.
no code implementations • CVPR 2020 • Zhuowan Li, Quan Tran, Long Mai, Zhe Lin, Alan Yuille
In this paper, we introduce a new task, context-aware group captioning, which aims to describe a group of target images in the context of another group of related reference images.
2 code implementations • Findings of the Association for Computational Linguistics 2020 • Khalil Mrini, Franck Dernoncourt, Quan Tran, Trung Bui, Walter Chang, Ndapa Nakashole
Finally, we find that the Label Attention heads learn relations between syntactic categories and show pathways to analyze errors.
Ranked #1 on Dependency Parsing on Penn Treebank
no code implementations • IJCNLP 2017 • Quan Tran, Andrew MacKinlay, Antonio Jimeno Yepes
Recurrent Neural Network models are the state-of-the-art for Named Entity Recognition (NER).