I am a Scientist at TCS Research, Kolkata. My research focus is application of machine learning and deep learning for natural language processing/understanding (NLP/NLU) tasks such as information extraction, question-answering, knowledge-base completion, text generation, machine translation, etc. I am also exploring the large language models (LLMs) for NLP/NLU tasks.

Previously, I was a postdoctoral researcher at IIT Kharagpur, where I worked on aspect-sentiment extraction, information extraction from material science research articles, causality extraction, and question-answering. I received my Ph.D. from the Department of Computer Science, National University of Singapore. My doctoral thesis is on relation extraction using deep neural networks from the text for the enrichment of knowledge bases.

Before joining the National University of Singapore, I did my bachelor's and masters in Computer Science & Engineering from Jadavpur University, Kolkata, India. I also worked as a software engineer at Hewlett-Packard India and PwC India for 5 years.



Education

2016 - 2020     Ph.D., Computer Science, National University of Singapore, Singapore
Thesis Title: Deep Neural Networks for Relation Extraction
Advisor: Prof. Hwee Tou Ng
2014 - 2016     M.E., Computer Scinece & Engineering, Jadavpur University, Kolkata, India
Thesis Title: Computer Aided Translation & Automatic Post Editing
Advisor: Assoc. Prof. Sudip Kumar Naskar
2005 - 2009     B.E., Computer Scinece & Engineering, Jadavpur University, Kolkata, India

Industry Experience

2012 - 2014     Senior Consultant, PricewaterhouseCoopers India, Kolkata, India
2009 - 2012     Software Engr I, Hewlett-Packard India Software Operations, Bangalore, India

Research Experience

2020 - 2021      Postdoctoral Researcher, Indian Institute of Technology Kharagpur, India
Advisor: Assoc. Prof. Pawan Goyal
2021 -      Scientist, TCS Research and Innovation, India

Research Interests

  • Natural Language Understanding
  • Deep Neural Networks
  • Information Extraction
  • Aspect-Sentiment Extraction
  • Causality Extraction
  • Question-Answering
  • Neural Machine Translation
  • Knowledge Base Completion

Publications

Few publications are listed here. For more, visit my google scholar page.
(* means equal contribution)
  • 2023
    • tagE: Enabling an Embodied Agent to Understand Human Instructions.
      Chayan Sarkar, Avik Mitra, Pradip Pramanick, and Tapas Nayak
      EMNLP 2023 Findings
      Paper

    • MatSciRE: Leveraging Pointer Networks to Automate Entity and Relation Extraction for Material Science Knowledge-base Construction.
      Ankan Mullick, Akash Ghosh, G Sai Chaitanya, Samir Ghui, Tapas Nayak, Seung-Cheol Lee, Satadeep Bhattacharjee, and Pawan Goyal
      Computational Materials Science, Elsevier, 2023
      Paper

    • Adapting Pre-trained Generative Models for Extractive Question Answering.
      Prabir Mallick, Tapas Nayak, and Indrajit Bhattacharya
      GEM workshop @ EMNLP 2023
      Paper

    • Do the Benefits of Joint Models for Relation Extraction Extend to Document-level Tasks?.
      Pratik Saini, Tapas Nayak, and Indrajit Bhattacharya
      IJCNLP-AACL 2023 (short)
      Paper

    • 90% F1 Score in Relational Triple Extraction: Is it Real ?.
      Pratik Saini, Samiran Pal, Tapas Nayak, and Indrajit Bhattacharya
      GenBench workshop @ EMNLP 2023
      Paper

  • 2022
    • Weakly Supervised Context-based Interview Question Generation.
      Samiran Pal, Kaamraan Khan, Avinash Kumar Singh, Subhasish Ghosh, Tapas Nayak, Girish Palshikar, and Indrajit Bhattacharya
      GEM workshop @ EMNLP 2022
      Paper

    • Unsupervised Generation of Long-form Technical Questions from Textbook Metadata using Structured Templates.
      Indrajit Bhattacharya, Subhasish Ghosh, Arpita Kundu, Pratik Saini, and Tapas Nayak
      PANDL workshop @ COLING 2022
      Paper

    • A Weak Supervision Approach for Predicting Difficulty of Technical Interview Questions.
      Arpita Kundu, Subhasish Ghosh, Pratik Saini, Tapas Nayak, and Indrajit Bhattacharya
      COLING 2022
      Paper

    • Exploring Generative Models for Joint Attribute Value Extraction from Product Titles.
      Kalyani Roy, Tapas Nayak, and Pawan Goyal
      ArXiv 2022
      Paper

    • Using Sentence-level Classification Helps Entity Extraction from Material Science Literature.
      Ankan Mullick, Shubhraneel Pal, Tapas Nayak, Seung-Cheol Lee, Satadeep Bhattacharjee, and Pawan Goyal
      LREC 2022
      Paper

    • FinRED: A dataset for Relation Extraction in Financial Domain.
      Soumya Sharma, Tapas Nayak, Arusarka Bose, Ajay Kumar Meena, Koustuv Dasgupta, Niloy Ganguly, and Pawan Goyal
      Companion Proceedings of the Web Conference 2022
      Paper

    • A Generative Approach for Financial Causality Extraction.
      Tapas Nayak, Soumya Sharma, Yash Butala, Koustuv Dasgupta, Pawan Goyal, and Niloy Ganguly
      FinWeb workshop of WWW 2022
      Paper

    • Investigating the Generative Approach for Question Answering in E-Commerce.
      Kalyani Roy, Vineeth Kumar Balapanuru, Tapas Nayak, and Pawan Goyal
      ECNLP workshop at ACL 2022
      Paper

  • 2021
    • PASTE: A Tagging-free Decoding Framework using Pointer Networks for Aspect Sentiment Triplet Extraction.
      Rajdeep Mukherjee*, Tapas Nayak*, Yash Butala, Sourangshu Bhattacharya, and Pawan Goyal
      EMNLP, 2021.
      Paper Code

    • Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey.
      Tapas Nayak, Navonil Majumder, Pawan Goyal, and Soujanya Poria
      Cognitive Computation, 2021.
      Paper

    • Aspect Sentiment Triplet Extraction Using Reinforcement Learning.
      Samson Yu Bai Jian, Tapas Nayak, Navonil Majumder, and Soujanya Poria
      30th ACM International Conference on Information and Knowledge Management (CIKM), 2021 (Short).
      Paper Code

    • Improving Distantly Supervised Relation Extraction with Self-Ensemble Noise Filtering.
      Tapas Nayak, Navonil Majumder, and Soujanya Poria
      Recent Advances in Natural Language Processing (RANLP), 2021.
      Paper Code

    • A Hierarchical Entity Graph Convolutional Network for Relation Extraction across Documents.
      Tapas Nayak and Hwee Tou Ng
      Recent Advances in Natural Language Processing (RANLP), 2021.
      Paper Code

  • 2020
    • Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation Extraction.
      Tapas Nayak and Hwee Tou Ng
      Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.
      Paper Code

  • 2019
    • Effective Attention Modeling for Neural Relation Extraction.
      Tapas Nayak and Hwee Tou Ng
      The SIGNLL Conference on Computational Natural Language Learning (CoNLL), 2019.
      Paper Code

  • 2016
    • CATaLog Online: A Web-based CAT Tool for Distributed Translation with Data Capture for APE and Translation Process Research.
      Santanu Pal, Sudip Naskar, Marcos Zampieri, Tapas Nayak, and Josef van Genabith
      26th International Conference on Computational Linguistics (COLING): System Demonstrations, Osaka, Japan, 2016.
      Paper

    • Beyond Translation Memories: Generating Translation Suggestions based on Parsing and POS Tagging.
      Tapas Nayak, Santanu Pal, Sudip Kumar Naskar, Sivaji Bandyopadhyay, and Josef van Genabith
      2nd Workshop on Natural Language Processing for Translation Memories (NLP4TM), Portorož, Slovenia, 2016.
      Paper

    • CATaLog Online: Porting a Post-editing Tool to the Web.
      Santanu Pal, Marcos Zampieri, Mihaela Vela, Tapas Nayak, Sudip Kumar Naskar, and Josef van Genabith
      10th International Conference on Language Resources and Evaluation (LREC), 2016.
      Paper

  • 2015
    • CATaLog: New Approaches to TM and Post Editing Interfaces.
      Tapas Nayak, Sudip Kumar Naskar, Santanu Pal, Marcos Zampieri, Mihaela Vela, and Josef van Genabith
      Workshop on Natural Language Processing for Translation Memories (NLP4TM), 2015.
      Paper