no code implementations • EMNLP 2020 • Avinash Swaminathan, Haimin Zhang, Debanjan Mahata, Rakesh Gosangi, Rajiv Ratn Shah, Amanda Stent
We observed that our model achieves state-of-the-art performance in the generation of abstractive keyphrases and is comparable to the best performing extractive techniques.
no code implementations • 15 Apr 2024 • Haimin Zhang, Min Xu
Intuitively, we can expect the generated embeddings become smooth asymptotically layerwisely, that is each layer of graph convolution generates a smoothed version of embeddings as compared to that generated by the previous layer.
no code implementations • 15 Apr 2024 • Haimin Zhang, Min Xu
To address this issue, we propose a neighbour-level message interaction information encoding method for improving graph representation learning.
no code implementations • 20 Apr 2023 • Yingqi Wang, Zhongqin Wang, J. Andrew Zhang, Haimin Zhang, Min Xu
Contact-free vital sign monitoring, which uses wireless signals for recognizing human vital signs (i. e, breath and heartbeat), is an attractive solution to health and security.
no code implementations • 2 Apr 2023 • Lu Huo, Jiahao Xia, Leijie Zhang, Haimin Zhang, Min Xu
More specifically, they overlook the contextual information across modalities of HSI and LiDAR and the intra-modality characteristics of LiDAR.
no code implementations • NAACL 2021 • Rakesh Gosangi, Ravneet Arora, Mohsen Gheisarieha, Debanjan Mahata, Haimin Zhang
In this paper, we study the importance of context in predicting the citation worthiness of sentences in scholarly articles.
no code implementations • 13 Mar 2021 • Jiahao Xia, Haimin Zhang, Shiping Wen, Shuo Yang, Min Xu
Moreover, we generate a cheap heatmap based on the face alignment result and fuse it with features to improve the performance of the other two tasks.
Ranked #28 on Face Alignment on WFLW
no code implementations • 8 Mar 2021 • Haimin Zhang, Min Xu
Based on this observation, we propose a method for counteracting adversarial perturbations to improve adversarial robustness.
1 code implementation • 20 Feb 2021 • Haimin Zhang, Min Xu, Guoqiang Zhang, Kenta Niwa
We show that applying stochastic scaling at the gradient level is complementary to that applied at the feature level to improve the overall performance.
no code implementations • 1 Jan 2021 • Haimin Zhang, Min Xu
We validate the proposed method on CIFAR-10 and CIFAR-100.
2 code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Shagun Uppal, Vivek Gupta, Avinash Swaminathan, Haimin Zhang, Debanjan Mahata, Rakesh Gosangi, Rajiv Ratn Shah, Amanda Stent
We further improve the performance by using a joint-objective for classification and textual entailment.
no code implementations • SEMEVAL 2020 • Sarthak Anand, Pradyumna Gupta, Hemant Yadav, Debanjan Mahata, Rakesh Gosangi, Haimin Zhang, Rajiv Ratn Shah
This paper presents our submission to the SemEval 2020 - Task 10 on emphasis selection in written text.
no code implementations • LREC 2020 • Swapnil Dhanwal, Hritwik Dutta, Hitesh Nankani, Nilay Shrivastava, Yaman Kumar, Junyi Jessy Li, Debanjan Mahata, Rakesh Gosangi, Haimin Zhang, Rajiv Ratn Shah, Am Stent, a
In this paper, we present a new corpus consisting of sentences from Hindi short stories annotated for five different discourse modes argumentative, narrative, descriptive, dialogic and informative.
no code implementations • 19 Oct 2019 • Dhruva Sahrawat, Debanjan Mahata, Mayank Kulkarni, Haimin Zhang, Rakesh Gosangi, Amanda Stent, Agniv Sharma, Yaman Kumar, Rajiv Ratn Shah, Roger Zimmermann
In this paper, we formulate keyphrase extraction from scholarly articles as a sequence labeling task solved using a BiLSTM-CRF, where the words in the input text are represented using deep contextualized embeddings.
1 code implementation • 24 Sep 2019 • Avinash Swaminathan, Raj Kuwar Gupta, Haimin Zhang, Debanjan Mahata, Rakesh Gosangi, Rajiv Ratn Shah
In this paper, we present a keyphrase generation approach using conditional Generative Adversarial Networks (GAN).
no code implementations • 2 Aug 2019 • Ozan İrsoy, Rakesh Gosangi, Haimin Zhang, Mu-Hsin Wei, Peter Lund, Duccio Pappadopulo, Brendan Fahy, Neophytos Nephytou, Camilo Ortiz
In this paper, we introduce a new model architecture, directed-acyclic-graph LSTM (DAG-LSTM) for DA classification.
1 code implementation • 19 Apr 2019 • Sarthak Anand, Debanjan Mahata, Kartik Aggarwal, Laiba Mehnaz, Simra Shahid, Haimin Zhang, Yaman Kumar, Rajiv Ratn Shah, Karan Uppal
In this paper we present our approach and the system description for Sub Task A of SemEval 2019 Task 9: Suggestion Mining from Online Reviews and Forums.
no code implementations • 19 Apr 2019 • Haimin Zhang, Debanjan Mahata, Simra Shahid, Laiba Mehnaz, Sarthak Anand, Yaman Singla, Rajiv Ratn Shah, Karan Uppal
In this paper we present our approach and the system description for Sub-task A and Sub Task B of SemEval 2019 Task 6: Identifying and Categorizing Offensive Language in Social Media.
no code implementations • 11 Jun 2018 • Haimin Zhang, Min Xu
This architecture forces the network to learn discriminative class-specific features by analyzing and comparing two input images.
no code implementations • 20 Mar 2016 • Haimin Zhang, Min Xu
By this way, static image features extracted from a pre-trained deep CNN and temporal information represented by DFT features are jointly considered for video emotion recognition.
no code implementations • 20 Mar 2016 • Haimin Zhang
In this way, static image features extracted from a pre-trained deep CNN and temporal information represented by DFT features are jointly considered for video classification.