About me

I am currently a Research Scientist at A*STAR Singapore, specializing in Natural Language Processing. Before joining A*STAR, I worked as a PostDoc with Prof. Mark Steedman and completed my PhD advised by Prof. Mirella Lapata at the Informatics Institute of the University of Edinburgh.

My PhD research focused on Natural Language Generation, specifically data-to-text generation. I developed techniques for generating long documents (more than 200 tokens) from tables of statistics as input. My thesis, titled “Data-to-text generation with Neural Planning”, explored novel strategies for neural content planning in long document generation. My PhD thesis received the Best Dissertation in Scotland award from SICSA Scotland. During my PhD, I also interned with the Summarization team at Google Research, London.

Before my PhD, I gained experience in various research positions:

• Research Assistant with Prof. Yue Zhang at the NLP lab of SUTD, Singapore.
• Research Engineer at the NLP lab of IIT Bombay, working with Prof. Pushpak Bhattacharyya.
• Technical Architect in the research division of a Software Product firm.

I completed my MS in Computer Science by Research at IIIT Hyderabad advised by Prof. Manish Shrivastava in February 2017. My thesis focused on “Transition-based techniques for Syntactic Linearization and Deep Input Linearization.”

News

• 25 Jan 2024: Introducing Airavata, Hindi Instruction-tuned LLM - Blog
• 24 Jan 2024: RomanSetu for unlocking multilingual capabilities of Large Language Models via Romanization - Preprint
• 21 Nov 2023: IndicTrans2 is accepted to Transactions of Machine Learning Research (TMLR) - Preprint
• 13 Nov 2023: VerityMath for applying unit consistency check for math problem solving - Preprint
• 9 Oct 2023: Two papers accepted to EMNLP. DecoMT is accepted to Main and CTQScorer to Findings - DecoMT Preprint - CTQScorer Preprint

Papers

For my latest publications, please visit my Google Scholar profile.

• VerityMath: Advancing Mathematical Reasoning by Self-Verification Through Unit Consistency Vernon Toh, Ratish Puduppully, Nancy F. Chen. 2023.
• Decomposed Prompting for Machine Translation Between Related Languages using Large Language Models Code
  Ratish Puduppully, Anoop Kunchukuttan, Raj Dabre, Ai Ti Aw, Nancy F. Chen. In Proceedings of EMNLP. 2023.
• CTQScorer: Combining Multiple Features for In-context Example Selection for Machine Translation Code
  Aswanth Kumar, Ratish Puduppully, Raj Dabre, Anoop Kunchukuttan. In Findings of EMNLP. 2023.
• IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages Code
  AI4Bharat, Jay Gala, Pranjal A. Chitale, Raghavan AK, Sumanth Doddapaneni, Varun Gumma, Aswanth Kumar, Janki Nawale, Anupama Sujatha, Ratish Puduppully, Vivek Raghavan, Pratyush Kumar, Mitesh M. Khapra, Raj Dabre, Anoop Kunchukuttan. In Transactions of Machine Learning Research (TMLR) (to appear). 2023.
• A Comprehensive Analysis of Adapter Efficiency Code
  Nandini Mundra, Sumanth Doddapaneni, Raj Dabre, Anoop Kunchukuttan, Ratish Puduppully, Mitesh M Khapra. 2023.
• Multi-Document Summarization with Centroid-Based Pretraining Code
  Ratish Surendran Puduppully, Parag Jain, Nancy Chen, Mark Steedman. In Proceedings of ACL. 2023.
• IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages Code
  Aman Kumar, Himani Shrotriya, Prachi Sahu, Raj Dabre, Ratish Puduppully, Anoop Kunchukuttan, Amogh Mishra, Mitesh M. Khapra, Pratyush Kumar. In Proceedings of EMNLP. 2022.
• Data-to-text Generation with Variational Sequential Planning. Code
  Ratish Puduppully and Yao Fu and Mirella Lapata. In Transactions of the Association for Computational Linguistics (TACL). 2022.
• IndicBART: A Pre-trained Model for Natural Language Generation of Indic Languages Code
  Raj Dabre, Himani Shrotriya, Anoop Kunchukuttan, Ratish Puduppully, Mitesh M. Khapra, Pratyush Kumar. In Findings of ACL. 2022.
• Data-to-text Generation with Macro Planning. Code
  Ratish Puduppully and Mirella Lapata. In Transactions of the Association for Computational Linguistics (TACL). 2021.
• University of Edinburgh's submission to the Document-level Generation and Translation Shared Task. Code
  Ratish Puduppully, Jonathan Mallinson, Mirella Lapata. In Proceedings of Workshop on Neural Generation and Translation, EMNLP. 2019.
• Data-to-text Generation with Entity Modeling. Code
  Ratish Puduppully, Li Dong, Mirella Lapata. In Proceedings of ACL. 2019.
• Data-to-Text Generation with Content Selection and Planning Code
  Ratish Puduppully, Li Dong, Mirella Lapata. In Proceedings of AAAI. 2019.
• Transition-Based Deep Input Linearization Code
  Ratish Puduppully, Yue Zhang and Manish Shrivastava. In Proceedings of EACL. 2017.
• Transition-Based Syntactic Linearization with Lookahead Features Code
  Ratish Puduppully, Yue Zhang and Manish Shrivastava. In Proceedings of NAACL. 2016.
• Brahmi-Net - An online system for transliteration and script conversion for Indian languages Code
  Anoop Kunchukuttan*, Ratish Puduppully* and Pushpak Bhattacharyya. In Proceedings of NAACL-HLT Demonstrations. 2015.
• Merging Verb Senses of Hindi WordNet using Word Embeddings Sudha Bhingardive, Ratish Puduppully, Dhirendra Singh and Pushpak Bhattacharyya. In Proceedings of International Conference on Natural Language Processing (ICON). 2014.
• The IIT Bombay SMT System for ICON 2014 Tools Contest Anoop Kunchukuttan, Ratish Puduppully, Rajen Chatterjee, Abhijit Mishra, Pushpak Bhattacharyya. In Proceedings of International Conference on Natural Language Processing (ICON) Tools Contest. 2014.