About Me

I am a computer science PhD student at the Massachusetts Institute of Technology (MIT) — studying artificial intelligence through natural language processing and machine learning. I am lucky to be advised by Jacob Andreas.

I work on improving sequence modeling for language processing and understanding. Languages exhibit some notion of compositionality (productivity and systematicity) whereas current neural language learners lack required inductive biases to achieve this data-efficiently. My recent work aims at understanding simple biases that will enable neural sequence models to achieve types of generalization that humans do

I am also interested in language supervision/grounding and worked on two recent projects: (i) using language to guide image classifiers to learn representations that enable learning of new classes (only with few samples) without forgetting the old ones, (ii) using language models to guide policy learning in a virtual home environment.





What learning algorithm is in-context learning? Investigations with linear models

Ekin Akyürek, Dale Schuurmans, Jacob Andreas*, Tengyu Ma*, Denny Zhou*
International Conference on Learning Representations, ICLR 2023 (oral)

Compositional Semantic Parsing with Large Language Models

Andrew Drozdov*, Nathanael Schärli*, Ekin Akyürek, Nathan Scales, Xinying Song, Xinyun Chen, Olivier Bousquet, Denny Zhou
International Conference on Learning Representations, ICLR 2023

Notes on Teaching GPT-3 Adding Numbers

Ekin Akyürek, Afra Feyza Akyürek
Blog Post

Tracing Knowledge in Language Models Back to the Training Data

Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu
Findings of the Conference on Empirical Methods in Natural Language Processing, EMNLP, 2022

Compositionality as Lexical Symmetry

Ekin Akyürek, Jacob Andreas

Pre-Trained Language Models for Interactive Decision-Making

Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu
Neural Information Processing Systems, Neurips, 2022 (oral)

Backpropagation through Back substitution with a Backslash

Ekin Akyürek, Alan Edelman, Bernie Wang (2021)
Neurips Differential Programming Workshop, 2021

Subspace Regularizers for Few-Shot Class Incremental Learning

Afra Feyza Akyürek, Ekin Akyürek, Derry Wijaya, Jacob Andreas (2021)
International Conference on Learning Representations, ICLR 2022

Lexicon Learning for Few-Shot Neural Sequence Modeling

Ekin Akyürek, Jacob Andreas (2021)
Annual Meeting of the Association for Computational Linguistics, ACL 2021 (oral)

Learning To Recombine and Resample Data For Compositional Generalization

Ekin Akyürek, Afra Feyza Akyürek, Jacob Andreas (2020)
International Conference on Learning Representations, ICLR 2021

Morphological Analysis Using Sequence Decoder

Ekin Akyürek*, Erenay Dayanık*, Deniz Yuret (2019)
Transactions of the Association for Computational Linguistics, TACL (also presented at EMNLP 2019)

Through the Glance Mug: A Familiar Artefact to Support Opportunistic Search in Meetings

Ahmet Börütecene, İdil Bostan, Ekin Akyürek, Alpay Sabuncuoğlu, İlker Temuzkuşu, Çağlar Genç, Tilbe Göksun, Oğuzhan Özcan (2018)
In Proceedings of the 12th International Conference on Tangible, Embedded and Embodied Interaction, TEI 2018, ACM