Hi! I’m a PhD student at the Language Technologies Institute in the School of Computer Science at Carnegie Mellon working with Daniel Fried. I’m broadly interested in natural language processing, machine learning, and program synthesis, especially in how these fields interact with linguistics and cognitive science.
I completed my undergraduate and master’s degrees at IIIT Hyderabad studying computer science and computational linguistics. I worked on program synthesis for linguistic rules for my master’s thesis, advised by Monojit Choudhury and Dipti Misra Sharma. I also spent the summer of 2021 as an intern at Chandar Research Lab at Mila working on continual learning for dialogue systems with Sarath Chandar, Prasanna Parthasarathi and others. I also work with Evan Pu and others on viewing program synthesis as a communicative task.
Feel free to get in touch if you want to chat about research! If you’re looking to apply to PhD programs in NLP, check out this page!
News
| 16 January 2024 | Our paper on training pragmatic program synthesizers has been accepted to appear at ICLR 2024! |
| 9 November 2023 | The paper I led on using pragmatics to train program synthesizers is up on arXiv! Super excited to be able to share this work. |
| 7 October 2023 | Justin's paper on using symbolic plans over representations inferred by code models will appear at EMNLP! |
| 1 September 2023 | New work on amortizing pragmatic program synthesis using rankings up on arXiv! |
| 23 July 2023 | Organizing the Workshop on Theory-of-Mind at ICML 2023 |
Publications
Generating Pragmatic Examples to Train Neural Program Synthesizers
Saujas Vaduguru,
Daniel Fried,
Yewen Pu
Twelfth International Conference on Learning Representations (ICLR), 2024.
Symbolic Planning and Code Generation for Grounded Dialogue
Justin T. Chiu,
Wenting Zhao,
Derek Chen,
Saujas Vaduguru,
Alexander M. Rush,
Daniel Fried
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.
Amortizing Pragmatic Program Synthesis with Rankings
Yewen Pu,
Saujas Vaduguru,
Priyan Vaithilingam,
Elena Glassman,
Daniel Fried
arXiv preprint, 2023.
Adapting to Gradual Distribution Shifts with Continual Weight Averaging
Jared Fernandez,
Saujas Vaduguru,
Sanket Vaibhav Mehta,
Yonatan Bisk,
Emma Strubell
Workshop on High-dimensional Learning Dynamics
40th International Conference on Machine Learning (ICML), 2023.
Probing Negation in Language Models
Shashwat Singh,
Shashwat Goel,
Saujas Vaduguru,
Ponnurangam Kumaraguru
8th Workshop on Representation Learning for NLP (RepL4NLP)
61st Annual Meeting of the Association for Computational Linguistics (ACL), 2023.
Stress Rules from Surface Forms
Saujas Vaduguru,
Partho Sarthi,
Dipti Misra Sharma,
Monojit Choudhury
International Conference on Natural Language Processing (ICON), 2021.
Efficient Pragmatic Program Synthesis with Informative Specifications
Saujas Vaduguru,
Kevin Ellis,
Yewen Pu
Workshop on Meaning in Context: Pragmatic Communication in Humans and Machines
35th Conference on Neural Information Processing Systems (NeurIPS), 2021.
[talk],
[code]
Sample-efficient Linguistic Generalizations through Program Synthesis: Experiments with Phonology Problems
Saujas Vaduguru,
Aalok Sathe,
Monojit Choudhury,
Dipti Misra Sharma
Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP), 2021.
[dataset]