no code implementations • WS 2016 • Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
However, medical records enclose patient Private Health Information (PHI) which can reveal the identities of the patients.
no code implementations • WS 2016 • Pracheta Sahoo, Asif Ekbal, Sriparna Saha, Diego Moll{\'a}, N, Kaushik an
Semi-supervised clustering is an attractive alternative for traditional (unsupervised) clustering in targeted applications.
no code implementations • EACL 2017 • Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
The proposed system is evaluated on three benchmark biomedical datasets such as GENIA, GENETAG, and AiMed.
no code implementations • ACL 2017 • Mohammed Hasanuzzaman, Sabyasachi Kamila, M Kaur, eep, Sriparna Saha, Asif Ekbal
Automatically estimating a user{'}s socio-economic profile from their language use in social media can significantly help social science research and various downstream applications ranging from business to politics.
no code implementations • NAACL 2018 • Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Amit Sheth
In this paper, we adopt a novel adversarial learning approach for our multi-task learning framework to learn the sentiment{'}s strengths expressed in a medical blog.
no code implementations • 5 Jul 2018 • Shweta Yadav, Ankit Kumar, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
In this paper, we present a novel method based on deep bidirectional long short-term memory (B-LSTM) technique that exploits word sequences and dependency path related information to identify PPI information from text.
no code implementations • 30 Jul 2018 • Shweta Yadav, Joy Sain, Amit Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
A large percentage of this population is actively engaged in health social networks to share health-related information.
no code implementations • COLING 2018 • Sayantan Mitra, Mohammed Hasanuzzaman, Sriparna Saha, Andy Way
Current paper explores the use of multi-view learning for search result clustering.
2 code implementations • 2 Apr 2019 • Syed Arbaaz Qureshi, Mohammed Hasanuzzaman, Sriparna Saha, Gaël Dias
We use this network to regress the depression level.
no code implementations • 16 May 2019 • Chanchal Suman, Somanath Tripathy, Sriparna Saha
We achieved an accuracy of 99. 83% for 20% testing data of NSL-KDD dataset and 99. 65% accuracy for 10-fold cross-validation on Kyoto dataset.
no code implementations • ACL 2019 • Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
The mining of adverse drug reaction (ADR) has a crucial role in the pharmacovigilance.
1 code implementation • 18 May 2020 • Shailesh Sridhar, Snehanshu Saha, Azhar Shaikh, Rahul Yedida, Sriparna Saha
We leveraged the functional property of Mean Square Error, which is Lipschitz continuous to compute learning rate in shallow neural networks.
2 code implementations • 19 May 2020 • Rohan Mohapatra, Snehanshu Saha, Carlos A. Coello Coello, Anwesh Bhattacharya, Soma S. Dhavala, Sriparna Saha
This paper introduces AdaSwarm, a novel gradient-free optimizer which has similar or even better performance than the Adam optimizer adopted in neural networks.
no code implementations • 19 May 2020 • Anubhav Jangra, Sriparna Saha, Adam Jatowt, Mohammad Hasanuzzaman
Significant development of communication technology over the past few years has motivated research in multi-modal summarization techniques.
no code implementations • ACL 2020 • Pratik Dutta, Sriparna Saha
As a first step towards enabling the development of multimodal approaches for PPI identification, we have developed two multi-modal datasets which are extensions and multi-modal versions of two popular benchmark PPI corpora (BioInfer and HRPD50).
no code implementations • ACL 2020 • Tulika Saha, Aditya Patra, Sriparna Saha, Pushpak Bhattacharyya
In this work, we address the role of \textit{both} multi-modality and emotion recognition (ER) in DAC.
no code implementations • International Joint Conference on Neural Networks (IJCNN) 2020 • Kanani, Chandresh S., Sriparna Saha, and Pushpak Bhattacharyya
The paragraphs generated from standard image captioning models lack in language diversity and contain redundant information.
no code implementations • 20 Sep 2020 • Shweta Yadav, Srivatsa Ramesh, Sriparna Saha, Asif Ekbal
Towards this, we model the relation extraction problem in multi-task learning (MTL) framework and introduce for the first time the concept of structured self-attentive network complemented with the adversarial learning approach for the prediction of relationships from the biomedical and clinical text.
no code implementations • 21 Sep 2020 • Shweta Yadav, Joy Prakash Sain, Amit Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
The diverse NLU views demonstrate its effectiveness on both the tasks and as well as on the individual disease to assess a user's health.
no code implementations • SEMEVAL 2020 • Sayanta Paul, Sriparna Saha, Mohammed Hasanuzzaman
This task has been organized for several languages, e. g., Arabic, Danish, English, Greek and Turkish.
no code implementations • SEMEVAL 2020 • Chandresh Kanani, Sriparna Saha, Pushpak Bhattacharyya
Emphasis selection is the task of choosing candidate words for emphasis, it helps in automatically designing posters and other media contents with written text.
1 code implementation • NAACL 2022 • Rahul Kumar, Sandeep Mathias, Sriparna Saha, Pushpak Bhattacharyya
To find out which traits work best for different types of essays, we conduct ablation tests for each of the essay traits.
Ranked #4 on Automated Essay Scoring on ASAP
no code implementations • ICON 2020 • Anubhav Jangra, Raghav Jain, Vaibhav Mavi, Sriparna Saha, Pushpak Bhattacharyya
The anthology of spoken languages today is inundated with textual information, necessitating the development of automatic summarization models.
no code implementations • NAACL 2021 • Tulika Saha, Apoorva Upadhyaya, Sriparna Saha, Pushpak Bhattacharyya
Experimental results indicate that the proposed framework boosts the performance of the primary task, i. e., TA classification (TAC) by benefitting from the two secondary tasks, i. e., Sentiment and Emotion Analysis compared to its uni-modal and single task TAC (tweet act classification) variants.
1 code implementation • Findings (ACL) 2021 • Sriram Pingali, Shweta Yadav, Pratik Dutta, Sriparna Saha
The recent advancement of pre-trained Transformer models has propelled the development of effective text mining models across various biomedical tasks.
1 code implementation • International Joint Conference on Neural Networks (IJCNN) 2021 • Chandresh S. Kanani, Sriparna Saha, Pushpak Bhattacharyya
Recently, many works are proposed on the generation of multi-sentence video descriptions.
Ranked #2 on Dense Video Captioning on ActivityNet Captions
no code implementations • 11 Sep 2021 • Anubhav Jangra, Sourajit Mukherjee, Adam Jatowt, Sriparna Saha, Mohammad Hasanuzzaman
The new era of technology has brought us to the point where it is convenient for people to share their opinions over an abundance of platforms.
no code implementations • 7 Dec 2021 • Manas Jain, Sriparna Saha, Pushpak Bhattacharyya, Gladvin Chinnadurai, Manish Kumar Vatsa
A transformer-based Grammar Error Correction model GECToR (2020), is used as a post-processing step for better fluency.
1 code implementation • 9 Dec 2021 • Anindya Sundar Das, Sriparna Saha
A comprehensive understanding of vision and language and their interrelation are crucial to realize the underlying similarities and differences between these modalities and to learn more generalized, meaningful representations.
no code implementations • 23 Jan 2022 • Raghav Jain, Vaibhav Mavi, Anubhav Jangra, Sriparna Saha
The task of automatic text summarization has gained a lot of traction due to the recent advancements in machine learning techniques.
1 code implementation • LREC 2022 • Muskan Garg, Chandni Saxena, Veena Krishnan, Ruchi Joshi, Sriparna Saha, Vijay Mago, Bonnie J Dorr
We introduce a new dataset for Causal Analysis of Mental health issues in Social media posts (CAMS).
no code implementations • 3 Dec 2022 • Raghav Jain, Anubhav Jangra, Sriparna Saha, Adam Jatowt
The internet has had a dramatic effect on the healthcare industry, allowing documents to be saved, shared, and managed digitally.
no code implementations • 13 Feb 2023 • Yash Verma, Anubhav Jangra, Raghvendra Kumar, Sriparna Saha
Significant developments in techniques such as encoder-decoder models have enabled us to represent information comprising multiple modalities.
no code implementations • 22 Aug 2023 • Anindya Sundar Das, Aravind Ajay, Sriparna Saha, Monowar Bhuyan
In this approach, the anomaly scores of normal examples are adjusted to closely resemble reference scores obtained from a prior distribution.
no code implementations • 11 Sep 2023 • Abhisek Tiwari, Muhammed Sinan, Kaushik Roy, Amit Sheth, Sriparna Saha, Pushpak Bhattacharyya
These lexical-based metrics have the following key limitations: (a) word-to-word matching without semantic consideration: It assigns the same credit for failure to generate 'nice' and 'rice' for 'good'.
1 code implementation • 27 Sep 2023 • Abhisek Tiwari, Anisha Saha, Sriparna Saha, Pushpak Bhattacharyya, Minakshi Dhar
We propose a knowledge-infused, multi-modal, multi-tasking medical domain identification and clinical conversation summary generation (MM-CliConSummation) framework.
no code implementations • 16 Dec 2023 • Akash Ghosh, Arkadeep Acharya, Raghav Jain, Sriparna Saha, Aman Chadha, Setu Sinha
This multimodal approach not only enhances the decision-making process in healthcare but also fosters a more nuanced understanding of patient queries, laying the groundwork for future research in personalized and responsive medical care
1 code implementation • 3 Jan 2024 • Akash Ghosh, Arkadeep Acharya, Prince Jha, Aniket Gaudgaul, Rajdeep Majumdar, Sriparna Saha, Aman Chadha, Raghav Jain, Setu Sinha, Shivani Agarwal
This work introduces the task of multimodal medical question summarization for codemixed input in a low-resource setting.
1 code implementation • 10 Jan 2024 • Mohit Tomar, Abhisek Tiwari, Tulika Saha, Prince Jha, Sriparna Saha
In recent times, there has been an increasing awareness about imminent environmental challenges, resulting in people showing a stronger dedication to taking care of the environment and nurturing green life.
1 code implementation • 10 Jan 2024 • Abhisek Tiwari, Shreyangshu Bera, Sriparna Saha, Pushpak Bhattacharyya, Samrat Ghosh
Over the past few years, the use of the Internet for healthcare-related tasks has grown by leaps and bounds, posing a challenge in effectively managing and processing information to ensure its efficient utilization.
1 code implementation • 17 Jan 2024 • Krishanu Maity, Prince Jha, Raghav Jain, Sriparna Saha, Pushpak Bhattacharyya
While plenty of research is going on to develop better models for cyberbullying detection in monolingual language, there is very little research on the code-mixed languages and explainability aspect of cyberbullying.
1 code implementation • 18 Jan 2024 • Prince Jha, Krishanu Maity, Raghav Jain, Apoorv Verma, Sriparna Saha, Pushpak Bhattacharyya
A Contrastive Language-Image Pretraining (CLIP) projection-based multimodal shared-private multitask approach has been proposed for visual and textual explanation of a meme.
no code implementations • 5 Feb 2024 • Pranab Sahoo, Ayush Kumar Singh, Sriparna Saha, Vinija Jain, Samrat Mondal, Aman Chadha
This approach leverages task-specific instructions, known as prompts, to enhance model efficacy without modifying the core model parameters.
no code implementations • 20 Feb 2024 • Akash Ghosh, Arkadeep Acharya, Sriparna Saha, Vinija Jain, Aman Chadha
The advent of Large Language Models (LLMs) has significantly reshaped the trajectory of the AI revolution.
no code implementations • ICON 2021 • Santosh Kumar Mishra, Darsh Kaushik, Sriparna Saha, Pushpak Bhattacharyya
The obtained results show the efficacy of the proposed methodology over the state-of-the-art methods.
no code implementations • ICON 2021 • Santosh Kumar Mishra, Sriparna Saha, Pushpak Bhattacharyya
The proposed method’s performance is compared with state-of-the-art methods in terms of BLEU scores and manual evaluation (in terms of adequacy and fluency).
no code implementations • LREC 2022 • Yash Verma, Anubhav Jangra, Sriparna Saha, Adam Jatowt, Dwaipayan Roy
Keyword extraction is an integral task for many downstream problems like clustering, recommendation, search and classification.
no code implementations • NAACL 2022 • Tulika Saha, Saichethan Reddy, Anindya Das, Sriparna Saha, Pushpak Bhattacharyya
Mental Health Disorders continue plaguing humans worldwide.
no code implementations • ICON 2020 • Soumitra Ghosh, Asif Ekbal, Pushpak Bhattacharyya, Sriparna Saha, Vipin Tyagi, Alka Kumar, Shikha Srivastava, Nitish Kumar
We propose a Hierarchical Attention-based deep neural network for Emotion Detection (HAtED).
no code implementations • ICON 2020 • Chanchal Suman, Aditya Gupta, Sriparna Saha, Pushpak Bhattacharyya
Automatic prediction of personality traits has many real-life applications, e. g., in forensics, recommender systems, personalized services etc..
Personality Trait Recognition by Face Recommendation Systems
no code implementations • ICON 2020 • Chanchal Suman, Jeetu Kumar, Sriparna Saha, Pushpak Bhattacharyya
Smart devices are often deployed in some edge-devices, which require quality solutions in limited amount of memory usage.
no code implementations • EMNLP (sdp) 2020 • Santosh Kumar Mishra, Harshavardhan Kundarapu, Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
The publication rate of scientific literature increases rapidly, which poses a challenge for researchers to keep themselves updated with new state-of-the-art.
no code implementations • EMNLP (sdp) 2020 • Saichethan Reddy, Naveen Saini, Sriparna Saha, Pushpak Bhattacharyya
In this paper, we present the IIIT Bhagalpur and IIT Patna team’s effort to solve the three shared tasks namely, CL-SciSumm 2020, CL-LaySumm 2020, LongSumm 2020 at SDP 2020.