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Tirthankar Ghosal
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2020 – today
- 2024
- [j15]Prabhat Kumar Bharti, Tirthankar Ghosal, Mayank Agarwal, Asif Ekbal:
PEERRec: An AI-based approach to automatically generate recommendations and predict decisions in peer review. Int. J. Digit. Libr. 25(1): 55-72 (2024) - [j14]Rina Kumari, Vipin Gupta, Nischal Ashok, Tirthankar Ghosal, Asif Ekbal:
Emotion aided multi-task framework for video embedded misinformation detection. Multim. Tools Appl. 83(12): 37161-37185 (2024) - [j13]Tirthankar Ghosal, Kamal Kaushik Varanasi, Valia Kordoni:
A Deep Multi-Tasking Approach Leveraging on Cited-Citing Paper Relationship For Citation Intent Classification. Scientometrics 129(2): 767-783 (2024) - [c52]Sandeep Kumar, Guneet Singh Kohli, Tirthankar Ghosal, Asif Ekbal:
Longform Multimodal Lay Summarization of Scientific Papers: Towards Automatically Generating Science Blogs from Research Articles. LREC/COLING 2024: 10790-10801 - [i7]Yuan-Sen Ting, Tuan Dung Nguyen, Tirthankar Ghosal, Rui Pan, Hardik Arora, Zechang Sun, Tijmen de Haan, Nesar Ramachandra, Azton Wells, Sandeep Madireddy, Alberto Accomazzi:
AstroMLab 1: Who Wins Astronomy Jeopardy!? CoRR abs/2407.11194 (2024) - [i6]Kartheik Iyer, Mikaeel Yunus, Charles O'Neill, Christine Ye, Alina Hyk, Kiera McCormick, Ioana Ciuca, John F. Wu, Alberto Accomazzi, Simone Astarita, Rishabh Chakrabarty, Jesse Cranney, Anjalie Field, Tirthankar Ghosal, Michele Ginolfi, Marc Huertas-Company, Maja Jablonska, Sandor Kruk, Huiling Liu, Gabriel Marchidan, Rohit Mistry, Jill P. Naiman, Joshua E. G. Peek, Mugdha Polimera, Sergio J. Rodríguez Méndez, Kevin Schawinski, Sanjib Sharma, Michael J. Smith, Yuan-Sen Ting, Mike Walmsley:
pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy. CoRR abs/2408.01556 (2024) - 2023
- [j12]Rina Kumari, Nischal Ashok, Pawan Kumar Agrawal, Tirthankar Ghosal, Asif Ekbal:
Identifying multimodal misinformation leveraging novelty detection and emotion recognition. J. Intell. Inf. Syst. 61(3): 673-694 (2023) - [j11]Sandeep Kumar, Tirthankar Ghosal, Asif Ekbal:
DeepMetaGen: an unsupervised deep neural approach to generate template-based meta-reviews leveraging on aspect category and sentiment analysis from peer reviews. Int. J. Digit. Libr. 24(4): 263-281 (2023) - [c51]Sandeep Kumar, Tirthankar Ghosal, Asif Ekbal:
When Reviewers Lock Horns: Finding Disagreements in Scientific Peer Reviews. EMNLP 2023: 16693-16704 - [c50]Sandeep Kumar, Guneet Singh Kohli, Tirthankar Ghosal, Asif Ekbal:
MuP-SciDocSum: Leveraging Multi-perspective Peer Review Summaries for Scientific Document Summarization. ICADL (2) 2023: 250-267 - [c49]Tirthankar Ghosal, Ondrej Bojar, Marie Hledíková, Tom Kocmi, Anna Nedoluzhko:
Overview of the Second Shared Task on Automatic Minuting (AutoMin) at INLG 2023. INLG (Generation Challenges) 2023: 138-167 - [c48]Hardik Arora, Kartik Shinde, Tirthankar Ghosal:
Deciphering the Reviewer's Aspectual Perspective: A Joint Multitask Framework for Aspect and Sentiment Extraction from Scholarly Peer Reviews. JCDL 2023: 35-46 - [c47]Hamed Alhoori, Edward A. Fox, Ingo Frommholz, Haiming Liu, Corinna Coupette, Bastian Rieck, Tirthankar Ghosal, Jian Wu:
Who can Submit an Excellent Review for this Manuscript in the Next 30 Days? - Peer Reviewing in the Age of Overload. JCDL 2023: 319-320 - [c46]Rajeev Verma, Tirthankar Ghosal, Saprativa Bhattacharjee, Asif Ekbal, Pushpak Bhattacharyya:
ReviVal: Towards Automatically Evaluating the Informativeness of Peer Reviews. SIGIR-AP 2023: 95-103 - [i5]Sandeep Kumar, Tirthankar Ghosal, Asif Ekbal:
When Reviewers Lock Horn: Finding Disagreement in Scientific Peer Reviews. CoRR abs/2310.18685 (2023) - 2022
- [j10]Tirthankar Ghosal, Tanik Saikh, Tameesh Biswas, Asif Ekbal, Pushpak Bhattacharyya:
Novelty Detection: A Perspective from Natural Language Processing. Comput. Linguistics 48(1): 77-117 (2022) - [j9]Rina Kumari, Nischal Ashok, Tirthankar Ghosal, Asif Ekbal:
What the fake? Probing misinformation detection standing on the shoulder of novelty and emotion. Inf. Process. Manag. 59(1): 102740 (2022) - [j8]Tanik Saikh, Tirthankar Ghosal, Amish Mittal, Asif Ekbal, Pushpak Bhattacharyya:
ScienceQA: a novel resource for question answering on scholarly articles. Int. J. Digit. Libr. 23(3): 289-301 (2022) - [c45]Ashish Rana, Deepanshu Khanna, Tirthankar Ghosal, Muskaan Singh, Harpreet Singh, Prashant Singh Rana:
RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim Verification. SDU@AAAI 2022 - [c44]Arman Cohan, Guy Feigenblat, Dayne Freitag, Tirthankar Ghosal, Drahomira Herrmannova, Petr Knoth, Kyle Lo, Philipp Mayr, Michal Shmueli-Scheuer, Anita de Waard, Lucy Lu Wang:
Overview of the Third Workshop on Scholarly Document Processing. SDP@COLING 2022: 1-6 - [c43]Kartik Shinde, Trinita Roy, Tirthankar Ghosal:
An Extractive-Abstractive Approach for Multi-document Summarization of Scientific Articles for Literature Review. SDP@COLING 2022: 204-209 - [c42]Arman Cohan, Guy Feigenblat, Tirthankar Ghosal, Michal Shmueli-Scheuer:
Overview of the First Shared Task on Multi Perspective Scientific Document Summarization (MuP). SDP@COLING 2022: 263-267 - [c41]Prabhat Kumar Bharti, Tirthankar Ghosal, Mayank Agrawal, Asif Ekbal:
How Confident Was Your Reviewer? Estimating Reviewer Confidence from Peer Review Texts. DAS 2022: 126-139 - [c40]Asheesh Kumar, Tirthankar Ghosal, Saprativa Bhattacharjee, Asif Ekbal:
Investigations on Meta Review Generation from Peer Review Texts Leveraging Relevant Sub-tasks in the Peer Review Pipeline. TPDL 2022: 216-229 - [c39]Prabhat Kumar Bharti, Tirthankar Ghosal, Mayank Agarwal, Asif Ekbal:
BetterPR: A Dataset for Estimating the Constructiveness of Peer Review Comments. TPDL 2022: 500-505 - [c38]Prabhat Kumar Bharti, Tirthankar Ghosal, Mayank Agarwal, Asif Ekbal:
A Method for Automatically Estimating the Informativeness of Peer Reviews. ICON 2022: 280-289 - [c37]Jan Philip Wahle, Nischal Ashok, Terry Ruas, Norman Meuschke, Tirthankar Ghosal, Bela Gipp:
Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection. iConference (1) 2022: 381-392 - [c36]Vipin Gupta, Rina Kumari, Nischal Ashok, Tirthankar Ghosal, Asif Ekbal:
MMM: An Emotion and Novelty-aware Approach for Multilingual Multimodal Misinformation Detection. AACL/IJCNLP (Findings) 2022: 464-477 - [c35]Rajeev Verma, Rajarshi Roychoudhury, Tirthankar Ghosal:
The lack of theory is painful: Modeling Harshness in Peer Review Comments. AACL/IJCNLP (1) 2022: 925-935 - [c34]Sandeep Kumar, Hardik Arora, Tirthankar Ghosal, Asif Ekbal:
DeepASPeer: towards an aspect-level sentiment controllable framework for decision prediction from academic peer reviews. JCDL 2022: 29 - [c33]Tirthankar Ghosal, Kamal Kaushik Varanasi, Valia Kordoni:
HedgePeer: a dataset for uncertainty detection in peer reviews. JCDL 2022: 46 - [c32]Anna Nedoluzhko, Muskaan Singh, Marie Hledíková, Tirthankar Ghosal, Ondrej Bojar:
ELITR Minuting Corpus: A Novel Dataset for Automatic Minuting from Multi-Party Meetings in English and Czech. LREC 2022: 3174-3182 - [c31]Tirthankar Ghosal, Vignesh Edithal, Tanik Saikh, Saprativa Bhattacharjee, Asif Ekbal, Pushpak Bhattacharyya:
Novelty Detection in Community Question Answering Forums. PACLIC 2022: 525-532 - [c30]Kartik Shinde, Tirthankar Ghosal, Muskaan Singh, Ondrej Bojar:
Automatic Minuting: A Pipeline Method for Generating Minutes from Multi-Party Meeting Proceedings. PACLIC 2022: 691-702 - [c29]Nidhir Bhavsar, Rishikesh Devanathan, Aakash Bhatnagar, Muskaan Singh, Petr Motlícek, Tirthankar Ghosal:
Team Innovators at SemEval-2022 for Task 8: Multi-Task Training with Hyperpartisan and Semantic Relation for Multi-Lingual News Article Similarity. SemEval@NAACL 2022: 1163-1170 - [c28]Prabhat Kumar Bharti, Asheesh Kumar, Tirthankar Ghosal, Mayank Agrawal, Asif Ekbal:
Can a Machine Generate a Meta-Review? How Far Are We? TSD 2022: 275-287 - [e2]Arman Cohan, Guy Feigenblat, Dayne Freitag, Tirthankar Ghosal, Drahomira Herrmannova, Petr Knoth, Kyle Lo, Philipp Mayr, Michal Shmueli-Scheuer, Anita de Waard, Lucy Lu Wang:
Proceedings of the Third Workshop on Scholarly Document Processing, SDP@COLING 2022, Gyeongju, Republic of Korea, October 12 - 17, 2022. Association for Computational Linguistics 2022 [contents] - [i4]Ashish Rana, Deepanshu Khanna, Muskaan Singh, Tirthankar Ghosal, Harpreet Singh, Prashant Singh Rana:
RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim Verification. CoRR abs/2202.02646 (2022) - 2021
- [j7]Rina Kumari, Nischal Ashok, Tirthankar Ghosal, Asif Ekbal:
Misinformation detection using multitask learning with mutual learning for novelty detection and emotion recognition. Inf. Process. Manag. 58(5): 102631 (2021) - [j6]Tirthankar Ghosal, Vignesh Edithal, Asif Ekbal, Pushpak Bhattacharyya, Srinivasa Satya Sameer Kumar Chivukula, George Tsatsaronis:
Is your document novel? Let attention guide you. An attention-based model for document-level novelty detection. Nat. Lang. Eng. 27(4): 427-454 (2021) - [j5]Tirthankar Ghosal, Piyush Tiwary, Robert M. Patton, Christopher G. Stahl:
Towards establishing a research lineage via identification of significant citations. Quant. Sci. Stud. 2(4): 1511-1528 (2021) - [j4]Tirthankar Ghosal, Muskaan Singh, Anja Nedoluzhko, Ondrej Bojar:
Report on the SIGDial 2021 special session on summarization of dialogues and multi-party meetings (SummDial). SIGIR Forum 55(2): 12:1-12:17 (2021) - [j3]Tirthankar Ghosal, Khalid Al Khatib, Yufang Hou, Anita de Waard, Dayne Freitag:
Report on the 1st workshop on argumentation knowledge graphs (ArgKG 2021) at AKBC 2021. SIGIR Forum 55(2): 19:1-19:12 (2021) - [j2]Tirthankar Ghosal:
Studies in aspects of peer review: novelty, scope, research lineage, review significance, and peer review outcome. SIGIR Forum 55(2): 26:1-26:2 (2021) - [c27]Tirthankar Ghosal, Muskaan Singh:
Towards Finding a Research Lineage Leveraging on Identification of Significant Citations. ASIST 2021: 456-460 - [c26]Basavraj Chinagundi, Muskaan Singh, Tirthankar Ghosal, Prashant Singh Rana, Guneet Singh Kohli:
Classification of Hate Offensive and Profane content from Tweets using an Ensemble of Deep Contextualized and Domain Specific Representations. FIRE (Working Notes) 2021: 491-500 - [c25]Sandeep Kumar, Tirthankar Ghosal, Asif Ekbal:
DataQuest: An Approach to Automatically Extract Dataset Mentions from Scientific Papers. ICADL 2021: 43-53 - [c24]Nishith Kotak, Anil K. Roy, Sourish Dasgupta, Tirthankar Ghosal:
A Consistency Analysis of Different NLP Approaches for Reviewer-Manuscript Matchmaking. ICADL 2021: 277-287 - [c23]Prabhat Kumar Bharti, Shashi Ranjan, Tirthankar Ghosal, Mayank Agrawal, Asif Ekbal:
PEERAssist: Leveraging on Paper-Review Interactions to Predict Peer Review Decisions. ICADL 2021: 421-435 - [c22]Komal Gupta, Ammaar Ahmad, Tirthankar Ghosal, Asif Ekbal:
ContriSci: A BERT-Based Multitasking Deep Neural Architecture to Identify Contribution Statements from Research Papers. ICADL 2021: 436-452 - [c21]Rajeev Verma, Kartik Shinde, Hardik Arora, Tirthankar Ghosal:
Attend to Your Review: A Deep Neural Network to Extract Aspects from Peer Reviews. ICONIP (6) 2021: 761-768 - [c20]Rina Kumari, Nischal Ashok, Tirthankar Ghosal, Asif Ekbal:
A Multitask Learning Approach for Fake News Detection: Novelty, Emotion, and Sentiment Lend a Helping Hand. IJCNN 2021: 1-8 - [c19]Asheesh Kumar, Tirthankar Ghosal, Asif Ekbal:
A Deep Neural Architecture for Decision-Aware Meta-Review Generation. JCDL 2021: 222-225 - [c18]Sandeep Kumar, Tirthankar Ghosal, Prabhat Kumar Bharti, Asif Ekbal:
Sharing is Caring! Joint Multitask Learning Helps Aspect-Category Extraction and Sentiment Detection in Scientific Peer Reviews. JCDL 2021: 270-273 - [c17]Guneet Singh Kohli, Prabsimran Kaur, Muskaan Singh, Tirthankar Ghosal, Prashant Singh Rana:
ARGUABLY @ AI Debater-NLPCC 2021 Task 3: Argument Pair Extraction from Peer Review and Rebuttals. NLPCC (2) 2021: 590-602 - [c16]Komal Gupta, Tirthankar Ghosal, Asif Ekbal:
A Neuro-Symbolic Approach for Question Answering on Research Articles. PACLIC 2021: 40-49 - [c15]Muskaan Singh, Tirthankar Ghosal, Ondrej Bojar:
An Empirical Performance Analysis of State-of-the-Art Summarization Models for Automatic Minuting. PACLIC 2021: 50-60 - [c14]Hardik Arora, Tirthankar Ghosal, Sandeep Kumar, Suraj Patwal, Phil Gooch:
INNOVATORS at SemEval-2021 Task-11: A Dependency Parsing and BERT-based model for Extracting Contribution Knowledge from Scientific Papers. SemEval@ACL/IJCNLP 2021: 502-510 - [i3]Jan Philip Wahle, Nischal Ashok, Terry Ruas, Norman Meuschke, Tirthankar Ghosal, Bela Gipp:
Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection. CoRR abs/2111.07819 (2021) - 2020
- [c13]Muthu Kumar Chandrasekaran, Guy Feigenblat, Dayne Freitag, Tirthankar Ghosal, Eduard H. Hovy, Philipp Mayr, Michal Shmueli-Scheuer, Anita de Waard:
Overview of the First Workshop on Scholarly Document Processing (SDP). SDP@EMNLP 2020: 1-6 - [c12]Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya:
An Empirical Study of Importance of Different Sections in Research Articles Towards Ascertaining Their Appropriateness to a Journal. ICADL 2020: 407-415 - [e1]Muthu Kumar Chandrasekaran, Anita de Waard, Guy Feigenblat, Dayne Freitag, Tirthankar Ghosal, Eduard H. Hovy, Petr Knoth, David Konopnicki, Philipp Mayr, Robert M. Patton, Michal Shmueli-Scheuer:
Proceedings of the First Workshop on Scholarly Document Processing, SDP@EMNLP 2020, Online, November 19, 2020. Association for Computational Linguistics 2020, ISBN 978-1-952148-70-5 [contents]
2010 – 2019
- 2019
- [j1]Tirthankar Ghosal:
Exploring the Implications of Artificial Intelligence in Various Aspects of Scholarly Peer Review. Bull. IEEE Tech. Comm. Digit. Libr. 15(1) (2019) - [c11]Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Pushpak Bhattacharyya:
DeepSentiPeer: Harnessing Sentiment in Review Texts to Recommend Peer Review Decisions. ACL (1) 2019: 1120-1130 - [c10]Tirthankar Ghosal, Abhishek Shukla, Asif Ekbal, Pushpak Bhattacharyya:
To Comprehend the New: On Measuring the Freshness of a Document. IJCNN 2019: 1-8 - [c9]Tirthankar Ghosal, Ashish Raj, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya:
A Deep Multimodal Investigation To Determine the Appropriateness of Scholarly Submissions. JCDL 2019: 227-236 - [c8]Tirthankar Ghosal, Ravi Sonam, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya:
Is the Paper Within Scope? Are You Fishing in the Right Pond? JCDL 2019: 237-240 - [c7]Tirthankar Ghosal, Ananya Chakraborty, Ravi Sonam, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya:
Incorporating Full Text and Bibliographic Features to Improve Scholarly Journal Recommendation. JCDL 2019: 374-375 - [c6]Tirthankar Ghosal, Debomit Dey, Avik Dutta, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya:
A Multiview Clustering Approach To Identify Out-of-Scope Submissions in Peer Review. JCDL 2019: 392-393 - [c5]Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Pushpak Bhattacharyya:
A Sentiment Augmented Deep Architecture to Predict Peer Review Outcomes. JCDL 2019: 414-415 - 2018
- [c4]Tirthankar Ghosal, Vignesh Edithal, Asif Ekbal, Pushpak Bhattacharyya, George Tsatsaronis, Srinivasa Satya Sameer Kumar Chivukula:
Novelty Goes Deep. A Deep Neural Solution To Document Level Novelty Detection. COLING 2018: 2802-2813 - [c3]Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya:
Investigating Impact Features in Editorial Pre-Screening of Research Papers. JCDL 2018: 333-334 - [c2]Tirthankar Ghosal, Amitra Salam, Swati Tiwary, Asif Ekbal, Pushpak Bhattacharyya:
TAP-DLND 1.0 : A Corpus for Document Level Novelty Detection. LREC 2018 - [i2]Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya:
An AI aid to the editors. Exploring the possibility of an AI assisted article classification system. CoRR abs/1802.01403 (2018) - [i1]Tirthankar Ghosal, Amitra Salam, Swati Tiwari, Asif Ekbal, Pushpak Bhattacharyya:
TAP-DLND 1.0 : A Corpus for Document Level Novelty Detection. CoRR abs/1802.06950 (2018) - 2017
- [c1]Tanik Saikh, Tirthankar Ghosal, Asif Ekbal, Pushpak Bhattacharyya:
Document Level Novelty Detection: Textual Entailment Lends a Helping Hand. ICON 2017: 131-140
Coauthor Index
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last updated on 2024-09-30 00:09 CEST by the dblp team
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