I am currently a 5th year CS PhD Student in the Stanford NLP Group, advised by Chris Manning, and a part-time student researcher at Google DeepMind.
I’m interested in building learning systems that can learn rich structures from limited data, and generalize (2, 3) beyond what they were trained on. These days, I’m thinking a lot about the role of memory in facilitating generalization.
I interned at Google Deepmind in Summer 2023 where I worked with Mandar Joshi, Kenton Lee and Pete Shaw. In Summer 2021, I interned with Marco Ribeiro and Scott Lundberg at Microsoft Research.
|September, 2023||Talk at AI2 titled “Understanding and Improving Generalization in Transformers”|
|May, 2023||Talk at MIT BCS titled “Transformers, Tree Structures and Generalization”|
|May, 2022||Talk about Language Patching at the NL Supervision Workshop at ACL 2022 in Dublin, in person!|
|February, 2022||Talk about using Language Supervision in ML (1, 2) at Apple Siri|
- Characterizing intrinsic compositionality in transformers with Tree ProjectionsIn The Eleventh International Conference on Learning Representations , 2023
- Grokking of Hierarchical Structure in Vanilla TransformersIn Annual Meeting of the Association for Computational Linguistics, 2023
- Fixing Model Bugs with Natural Language PatchesIn Conference on Empirical Methods in Natural Language Processing, 2022
- ExpBERT: Representation Engineering with Natural Language ExplanationsIn Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020
- Systematic Generalization: What Is Required and Can It Be Learned?In International Conference on Learning Representations, Jul 2019