Tapas Nayak

Research Experience

Apr, 2026 - Present	Assistant Professor, Indian Institute of Technology Roorkee, India
Nov, 2021 - Apr, 2026	Research Scientist, TCS Research, India
Sept, 2020 - Oct, 2021	Postdoctoral Researcher, Indian Institute of Technology Kharagpur, India Advisor: Prof. Pawan Goyal

Industry Experience

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

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

Research Interests Natural Language Understanding Deep Neural Networks Information Extraction Aspect-Sentiment Extraction Causality Extraction Question-Answering Neural Machine Translation Knowledge Graph Completion

Publications

Few publications are listed here. For more, visit my Google Scholar page.
(* means equal contribution)

• 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.
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• Effective Attention Modeling for Neural Relation Extraction.
  Tapas Nayak and Hwee Tou Ng
  The SIGNLL Conference on Computational Natural Language Learning (CoNLL), 2019.
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• Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey.
  Tapas Nayak, Navonil Majumder, Pawan Goyal, and Soujanya Poria
  Cognitive Computation, 2021.
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• 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.
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• 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.
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• 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)
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• Exploring Generative Models for Joint Attribute Value Extraction from Product Titles.
  Kalyani Roy, Tapas Nayak, and Pawan Goyal
  ArXiv 2022
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• 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
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• 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).
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• 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.
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• tagE: Enabling an Embodied Agent to Understand Human Instructions.
  Chayan Sarkar, Avik Mitra, Pradip Pramanick, and Tapas Nayak
  EMNLP 2023 Findings
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• 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
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• Adapting Pre-trained Generative Models for Extractive Question Answering.
  Prabir Mallick, Tapas Nayak, and Indrajit Bhattacharya
  GEM workshop @ EMNLP 2023
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• 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
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• 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
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• A Weak Supervision Approach for Predicting Difficulty of Technical Interview Questions.
  Arpita Kundu, Subhasish Ghosh, Pratik Saini, Tapas Nayak, and Indrajit Bhattacharya
  COLING 2022
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