Document Level Novelty Detection: Textual Entailment Lends a Helping Hand. - Tanik Saikh; Tirthankar Ghosal; Asif Ekbal; Pushpak Bhattacharyya (ICON, 2017)

Novelty Goes Deep. A Deep Neural Solution To Document Level Novelty Detection. - Tirthankar Ghosal; Vignesh Edithal; Asif Ekbal; Pushpak Bhattacharyya; George Tsatsaronis 001; Srinivasa Satya Sameer Kumar Chivukula (COLING, 2018)

Investigating Impact Features in Editorial Pre-Screening of Research Papers. - Tirthankar Ghosal; Rajeev Verma; Asif Ekbal; Sriparna Saha 001; Pushpak Bhattacharyya (JCDL, 2018)

TAP-DLND 1.0 : A Corpus for Document Level Novelty Detection. - Tirthankar Ghosal; Amitra Salam; Swati Tiwary; Asif Ekbal; Pushpak Bhattacharyya (LREC, 2018)

An AI aid to the editors. Exploring the possibility of an AI assisted article classification system. - Tirthankar Ghosal; Rajeev Verma; Asif Ekbal; Sriparna Saha 001; Pushpak Bhattacharyya (CoRR, 2018)

DeepSentiPeer: Harnessing Sentiment in Review Texts to Recommend Peer Review Decisions. - Tirthankar Ghosal; Rajeev Verma; Asif Ekbal; Pushpak Bhattacharyya (ACL (1), 2019)

To Comprehend the New: On Measuring the Freshness of a Document. - Tirthankar Ghosal; Abhishek Shukla; Asif Ekbal; Pushpak Bhattacharyya (IJCNN, 2019)

Incorporating Full Text and Bibliographic Features to Improve Scholarly Journal Recommendation. - Tirthankar Ghosal; Ananya Chakraborty; Ravi Sonam; Asif Ekbal; Sriparna Saha 001; Pushpak Bhattacharyya (JCDL, 2019)

A Multiview Clustering Approach To Identify Out-of-Scope Submissions in Peer Review. - Tirthankar Ghosal; Debomit Dey; Avik Dutta; Asif Ekbal; Sriparna Saha 001; Pushpak Bhattacharyya (JCDL, 2019)

A Deep Multimodal Investigation To Determine the Appropriateness of Scholarly Submissions. - Tirthankar Ghosal; Ashish Raj; Asif Ekbal; Sriparna Saha 001; Pushpak Bhattacharyya (JCDL, 2019)

Is the Paper Within Scope? Are You Fishing in the Right Pond? - Tirthankar Ghosal; Ravi Sonam; Asif Ekbal; Sriparna Saha 001; Pushpak Bhattacharyya (JCDL, 2019)

A Sentiment Augmented Deep Architecture to Predict Peer Review Outcomes. - Tirthankar Ghosal; Rajeev Verma; Asif Ekbal; Pushpak Bhattacharyya (JCDL, 2019)

Exploring the Implications of Artificial Intelligence in Various Aspects of Scholarly Peer Review. - Tirthankar Ghosal (Bull. IEEE Tech. Comm. Digit. Libr., 2019)

Overview of the First Workshop on Scholarly Document Processing (SDP). - Muthu Kumar Chandrasekaran; Guy Feigenblat; Dayne Freitag; Tirthankar Ghosal; Eduard H. Hovy; Philipp Mayr 001; Michal Shmueli-Scheuer; Anita de Waard (SDP@EMNLP, 2020)

An Empirical Study of Importance of Different Sections in Research Articles Towards Ascertaining Their Appropriateness to a Journal. - Tirthankar Ghosal; Rajeev Verma; Asif Ekbal; Sriparna Saha 001; Pushpak Bhattacharyya (ICADL, 2020)

Towards Finding a Research Lineage Leveraging on Identification of Significant Citations. - Tirthankar Ghosal; Muskaan Singh (ASIST, 2021)

Classification of Hate Offensive and Profane content from Tweets using an Ensemble of Deep Contextualized and Domain Specific Representations. - Basavraj Chinagundi; Muskaan Singh; Tirthankar Ghosal; Prashant Singh Rana; Guneet Singh Kohli (FIRE (Working Notes), 2021)

PEERAssist: Leveraging on Paper-Review Interactions to Predict Peer Review Decisions. - Prabhat Kumar Bharti; Shashi Ranjan; Tirthankar Ghosal; Mayank Agrawal; Asif Ekbal (ICADL, 2021)

ContriSci: A BERT-Based Multitasking Deep Neural Architecture to Identify Contribution Statements from Research Papers. - Komal Gupta; Ammaar Ahmad; Tirthankar Ghosal; Asif Ekbal (ICADL, 2021)

A Consistency Analysis of Different NLP Approaches for Reviewer-Manuscript Matchmaking. - Nishith Kotak; Anil K. Roy; Sourish Dasgupta; Tirthankar Ghosal (ICADL, 2021)

DataQuest: An Approach to Automatically Extract Dataset Mentions from Scientific Papers. - Sandeep Kumar 009; Tirthankar Ghosal; Asif Ekbal (ICADL, 2021)

Attend to Your Review: A Deep Neural Network to Extract Aspects from Peer Reviews. - Rajeev Verma; Kartik Shinde; Hardik Arora; Tirthankar Ghosal (ICONIP (6), 2021)

A Multitask Learning Approach for Fake News Detection: Novelty, Emotion, and Sentiment Lend a Helping Hand. - Rina Kumari; Nischal Ashok; Tirthankar Ghosal; Asif Ekbal (IJCNN, 2021)

Sharing is Caring! Joint Multitask Learning Helps Aspect-Category Extraction and Sentiment Detection in Scientific Peer Reviews. - Sandeep Kumar 009; Tirthankar Ghosal; Prabhat Kumar Bharti; Asif Ekbal (JCDL, 2021)

A Deep Neural Architecture for Decision-Aware Meta-Review Generation. - Asheesh Kumar; Tirthankar Ghosal; Asif Ekbal (JCDL, 2021)

ARGUABLY @ AI Debater-NLPCC 2021 Task 3: Argument Pair Extraction from Peer Review and Rebuttals. - Guneet Singh Kohli; Prabsimran Kaur; Muskaan Singh; Tirthankar Ghosal; Prashant Singh Rana (NLPCC (2), 2021)

A Neuro-Symbolic Approach for Question Answering on Research Articles. - Komal Gupta; Tirthankar Ghosal; Asif Ekbal (PACLIC, 2021)

An Empirical Performance Analysis of State-of-the-Art Summarization Models for Automatic Minuting. - Muskaan Singh; Tirthankar Ghosal; Ondrej Bojar (PACLIC, 2021)

INNOVATORS at SemEval-2021 Task-11: A Dependency Parsing and BERT-based model for Extracting Contribution Knowledge from Scientific Papers. - Hardik Arora; Tirthankar Ghosal; Sandeep Kumar 009; Suraj Patwal; Phil Gooch (SemEval@ACL/IJCNLP, 2021)

Misinformation detection using multitask learning with mutual learning for novelty detection and emotion recognition. - Rina Kumari; Nischal Ashok; Tirthankar Ghosal; Asif Ekbal (Inf. Process. Manag., 2021)

Is your document novel? Let attention guide you. An attention-based model for document-level novelty detection. - Tirthankar Ghosal; Vignesh Edithal; Asif Ekbal; Pushpak Bhattacharyya; Srinivasa Satya Sameer Kumar Chivukula; George Tsatsaronis 001 (Nat. Lang. Eng., 2021)

Towards establishing a research lineage via identification of significant citations. - Tirthankar Ghosal; Piyush Tiwary; Robert M. Patton; Christopher G. Stahl (Quant. Sci. Stud., 2021)

Studies in aspects of peer review: novelty, scope, research lineage, review significance, and peer review outcome. - Tirthankar Ghosal (SIGIR Forum, 2021)

Report on the 1st workshop on argumentation knowledge graphs (ArgKG 2021) at AKBC 2021. - Tirthankar Ghosal; Khalid Al Khatib; Yufang Hou 001; Anita de Waard; Dayne Freitag (SIGIR Forum, 2021)

Report on the SIGDial 2021 special session on summarization of dialogues and multi-party meetings (SummDial). - Tirthankar Ghosal; Muskaan Singh; Anja Nedoluzhko; Ondrej Bojar (SIGIR Forum, 2021)

RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim Verification. - Ashish Rana; Deepanshu Khanna; Tirthankar Ghosal; Muskaan Singh; Harpreet Singh; Prashant Singh Rana (SDU@AAAI, 2022)

Overview of the Third Workshop on Scholarly Document Processing. - Arman Cohan; Guy Feigenblat; Dayne Freitag; Tirthankar Ghosal; Drahomira Herrmannova; Petr Knoth; Kyle Lo; Philipp Mayr 001; Michal Shmueli-Scheuer; Anita de Waard; Lucy Lu Wang (SDP@COLING, 2022)

Overview of the First Shared Task on Multi Perspective Scientific Document Summarization (MuP). - Arman Cohan; Guy Feigenblat; Tirthankar Ghosal; Michal Shmueli-Scheuer (SDP@COLING, 2022)

An Extractive-Abstractive Approach for Multi-document Summarization of Scientific Articles for Literature Review. - Kartik Shinde; Trinita Roy; Tirthankar Ghosal (SDP@COLING, 2022)

How Confident Was Your Reviewer? Estimating Reviewer Confidence from Peer Review Texts. - Prabhat Kumar Bharti; Tirthankar Ghosal; Mayank Agrawal; Asif Ekbal (DAS, 2022)

BetterPR: A Dataset for Estimating the Constructiveness of Peer Review Comments. - Prabhat Kumar Bharti; Tirthankar Ghosal; Mayank Agarwal; Asif Ekbal (TPDL, 2022)

Investigations on Meta Review Generation from Peer Review Texts Leveraging Relevant Sub-tasks in the Peer Review Pipeline. - Asheesh Kumar; Tirthankar Ghosal; Saprativa Bhattacharjee; Asif Ekbal (TPDL, 2022)

A Method for Automatically Estimating the Informativeness of Peer Reviews. - Prabhat Kumar Bharti; Tirthankar Ghosal; Mayank Agarwal; Asif Ekbal (ICON, 2022)

Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection. - Jan Philip Wahle; Nischal Ashok; Terry Ruas; Norman Meuschke; Tirthankar Ghosal; Bela Gipp (iConference (1), 2022)

MMM: An Emotion and Novelty-aware Approach for Multilingual Multimodal Misinformation Detection. - Vipin Gupta; Rina Kumari; Nischal Ashok; Tirthankar Ghosal; Asif Ekbal (AACL/IJCNLP (Findings), 2022)

The lack of theory is painful: Modeling Harshness in Peer Review Comments. - Rajeev Verma; Rajarshi Roychoudhury; Tirthankar Ghosal (AACL/IJCNLP (1), 2022)

HedgePeer: a dataset for uncertainty detection in peer reviews. - Tirthankar Ghosal; Kamal Kaushik Varanasi; Valia Kordoni (JCDL, 2022)

DeepASPeer: towards an aspect-level sentiment controllable framework for decision prediction from academic peer reviews. - Sandeep Kumar 009; Hardik Arora; Tirthankar Ghosal; Asif Ekbal (JCDL, 2022)

ELITR Minuting Corpus: A Novel Dataset for Automatic Minuting from Multi-Party Meetings in English and Czech. - Anna Nedoluzhko; Muskaan Singh; Marie Hledíková; Tirthankar Ghosal; Ondrej Bojar (LREC, 2022)

Novelty Detection in Community Question Answering Forums. - Tirthankar Ghosal; Vignesh Edithal; Tanik Saikh; Saprativa Bhattacharjee; Asif Ekbal; Pushpak Bhattacharyya (PACLIC, 2022)

Automatic Minuting: A Pipeline Method for Generating Minutes from Multi-Party Meeting Proceedings. - Kartik Shinde; Tirthankar Ghosal; Muskaan Singh; Ondrej Bojar (PACLIC, 2022)

Team Innovators at SemEval-2022 for Task 8: Multi-Task Training with Hyperpartisan and Semantic Relation for Multi-Lingual News Article Similarity. - Nidhir Bhavsar; Rishikesh Devanathan; Aakash Bhatnagar; Muskaan Singh; Petr Motlícek; Tirthankar Ghosal (SemEval@NAACL, 2022)

Can a Machine Generate a Meta-Review? How Far Are We? - Prabhat Kumar Bharti; Asheesh Kumar; Tirthankar Ghosal; Mayank Agrawal; Asif Ekbal (TSD, 2022)

Novelty Detection: A Perspective from Natural Language Processing. - Tirthankar Ghosal; Tanik Saikh; Tameesh Biswas; Asif Ekbal; Pushpak Bhattacharyya (Comput. Linguistics, 2022)

What the fake? Probing misinformation detection standing on the shoulder of novelty and emotion. - Rina Kumari; Nischal Ashok; Tirthankar Ghosal; Asif Ekbal (Inf. Process. Manag., 2022)

ScienceQA: a novel resource for question answering on scholarly articles. - Tanik Saikh; Tirthankar Ghosal; Amish Mittal; Asif Ekbal; Pushpak Bhattacharyya (Int. J. Digit. Libr., 2022)

When Reviewers Lock Horns: Finding Disagreements in Scientific Peer Reviews. - Sandeep Kumar 009; Tirthankar Ghosal; Asif Ekbal (EMNLP, 2023)

MuP-SciDocSum: Leveraging Multi-perspective Peer Review Summaries for Scientific Document Summarization. - Sandeep Kumar 009; Guneet Singh Kohli; Tirthankar Ghosal; Asif Ekbal (ICADL (2), 2023)

Overview of the Second Shared Task on Automatic Minuting (AutoMin) at INLG 2023. - Tirthankar Ghosal; Ondrej Bojar; Marie Hledíková; Tom Kocmi; Anna Nedoluzhko (INLG (Generation Challenges), 2023)

Who can Submit an Excellent Review for this Manuscript in the Next 30 Days? - Peer Reviewing in the Age of Overload. - Hamed Alhoori; Edward A. Fox; Ingo Frommholz; Haiming Liu 002; Corinna Coupette; Bastian Rieck; Tirthankar Ghosal; Jian Wu 006 (JCDL, 2023)

Deciphering the Reviewer's Aspectual Perspective: A Joint Multitask Framework for Aspect and Sentiment Extraction from Scholarly Peer Reviews. - Hardik Arora; Kartik Shinde; Tirthankar Ghosal (JCDL, 2023)

ReviVal: Towards Automatically Evaluating the Informativeness of Peer Reviews. - Rajeev Verma; Tirthankar Ghosal; Saprativa Bhattacharjee; Asif Ekbal; Pushpak Bhattacharyya (SIGIR-AP, 2023)

When Reviewers Lock Horn: Finding Disagreement in Scientific Peer Reviews. - Sandeep Kumar 009; Tirthankar Ghosal; Asif Ekbal (CoRR, 2023)

Identifying multimodal misinformation leveraging novelty detection and emotion recognition. - Rina Kumari; Nischal Ashok; Pawan Kumar Agrawal; Tirthankar Ghosal; Asif Ekbal (J. Intell. Inf. Syst., 2023)

DeepMetaGen: an unsupervised deep neural approach to generate template-based meta-reviews leveraging on aspect category and sentiment analysis from peer reviews. - Sandeep Kumar 009; Tirthankar Ghosal; Asif Ekbal (Int. J. Digit. Libr., 2023)

Longform Multimodal Lay Summarization of Scientific Papers: Towards Automatically Generating Science Blogs from Research Articles. - Sandeep Kumar 009; Guneet Singh Kohli; Tirthankar Ghosal; Asif Ekbal (LREC/COLING, 2024)

'Quis custodiet ipsos custodes?' Who will watch the watchmen? On Detecting AI-generated peer-reviews. - Sandeep Kumar 009; Mohit Sahu; Vardhan Gacche; Tirthankar Ghosal; Asif Ekbal (EMNLP, 2024)

AstroMLab 2: AstroLLaMA-2-70B Model and Benchmarking Specialised LLMs for Astronomy. - Rui Pan 002; Tuan Dung Nguyen; Hardik Arora; Alberto Accomazzi; Tirthankar Ghosal; Yuan-Sen Ting (SC Workshops, 2024)

pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy. - 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; et al. (CoRR, 2024)

Can Large Language Models Unlock Novel Scientific Research Ideas? - Sandeep Kumar 009; Tirthankar Ghosal; Vinayak Goyal; Asif Ekbal (CoRR, 2024)

A Deep Multi-Tasking Approach Leveraging on Cited-Citing Paper Relationship For Citation Intent Classification. - Tirthankar Ghosal; Kamal Kaushik Varanasi; Valia Kordoni (Scientometrics, 2024)

PEERRec: An AI-based approach to automatically generate recommendations and predict decisions in peer review. - Prabhat Kumar Bharti; Tirthankar Ghosal; Mayank Agarwal; Asif Ekbal (Int. J. Digit. Libr., 2024)

Emotion aided multi-task framework for video embedded misinformation detection. - Rina Kumari; Vipin Gupta; Nischal Ashok; Tirthankar Ghosal; Asif Ekbal (Multim. Tools Appl., 2024)

Towards automated meta-review generation via an NLP/ML pipeline in different stages of the scholarly peer review process. - Asheesh Kumar; Tirthankar Ghosal; Saprativa Bhattacharjee; Asif Ekbal (Int. J. Digit. Libr., 2024)

A BERT-based sequential deep neural architecture to identify contribution statements and extract phrases for triplets from scientific publications. - Komal Gupta; Ammaar Ahmad; Tirthankar Ghosal; Asif Ekbal (Int. J. Digit. Libr., 2024)

SciND: a new triplet-based dataset for scientific novelty detection via knowledge graphs. - Komal Gupta; Ammaar Ahmad; Tirthankar Ghosal; Asif Ekbal (Int. J. Digit. Libr., 2024)

MixRevDetect: Towards Detecting AI-Generated Content in Hybrid Peer Reviews. - Sandeep Kumar 009; Samarth Garg; Sagnik Sengupta; Tirthankar Ghosal; Asif Ekbal (NAACL (Short Papers), 2025)

Toward Automatic Dataset Discovery From Scientific Publications. - Sandeep Kumar 009; Tirthankar Ghosal; Asif Ekbal (IEEE Access, 2025)

AstroMLab 1: Who wins astronomy jeopardy!? - Yuan-Sen Ting; Tuan Dung Nguyen; Tirthankar Ghosal; Rui Pan 002; Hardik Arora; Zechang Sun; Tijmen de Haan; Nesar Ramachandra; Azton Wells; Sandeep Madireddy; Alberto Accomazzi (Astron. Comput., 2025)

chatHPC: Empowering HPC users with large language models. - Junqi Yin; Jesse Hines; Emily Herron; Tirthankar Ghosal; Hong Liu; Suzanne Prentice; Vanessa Lama; Feiyi Wang (J. Supercomput., 2025)

A Survey on Hypothesis Generation for Scientific Discovery in the Era of Large Language Models. - Atilla Kaan Alkan; Shashwat Sourav; Maja Jablonska; Simone Astarita; Rishabh Chakrabarty; Nikhil Garuda; Pranav Khetarpal; Maciej Pióro; Dimitrios Tanoglidis; Kartheik Iyer; Mugdha Polimera; Michael J. Smith 013; et al. (CoRR, 2025)

Sparks of Science: Hypothesis Generation Using Structured Paper Data. - Charles O'Neill; Tirthankar Ghosal; Roberta Raileanu; Mike Walmsley; Thang D. Bui; Kevin Schawinski; Ioana Ciuca (CoRR, 2025)

AstroMLab 4: Benchmark-Topping Performance in Astronomy Q&A with a 70B-Parameter Domain-Specialized Reasoning Model. - Tijmen de Haan; Yuan-Sen Ting; Tirthankar Ghosal; Tuan Dung Nguyen; Alberto Accomazzi; Emily Herron; Vanessa Lama; Rui Pan 002; Azton Wells; Nesar Ramachandra (CoRR, 2025)

A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions. - Agada Joseph Oche; Ademola Glory Folashade; Tirthankar Ghosal; Arpan Biswas (CoRR, 2025)

PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflows. - Renan Souza 001; Amal Gueroudji; Stephen DeWitt; Daniel Rosendo; Tirthankar Ghosal; Robert B. Ross; Prasanna Balaprakash; Rafael Ferreira da Silva (CoRR, 2025)