Peter Shaw

Selected Publications

Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers
Peter Shaw, James Cohan, Jacob Eisenstein, Kristina Toutanova
Preprint

ALTA: Compiler-Based Analysis of Transformers
Peter Shaw, James Cohan, Jacob Eisenstein, Kenton Lee, Jonathan Berant, Kristina Toutanova
TMLR 2025 · Code

ProtEx: A Retrieval-Augmented Approach for Protein Function Prediction
Peter Shaw, Bhaskar Gurram, David Belanger, Andreea Gane, Maxwell L Bileschi, Lucy J Colwell, Kristina Toutanova, Ankur P Parikh
MLCB 2025 (Oral) · Code

From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces
Peter Shaw^*, Mandar Joshi^*, James Cohan, Jonathan Berant, Panupong Pasupat, Hexiang Hu, Urvashi Khandelwal, Kenton Lee, Kristina Toutanova
NeurIPS 2023 (Spotlight) · Code

QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations
Chaitanya Malaviya, Peter Shaw, Ming-Wei Chang, Kenton Lee, Kristina Toutanova
ACL 2023 · Outstanding Paper Award · Code · Dataset

Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding
Kenton Lee^*, Mandar Joshi^*, Iulia Turc, Hexiang Hu, Fangyu Liu, Julian Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, Kristina Toutanova
ICML 2023 · Code

Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing
Linlu Qiu, Peter Shaw, Panupong Pasupat, Tianze Shi, Jonathan Herzig, Emily Pitler, Fei Sha, Kristina Toutanova
EMNLP 2022

Improving Compositional Generalization with Latent Structure and Data Augmentation
Linlu Qiu^*, Peter Shaw^*, Panupong Pasupat, Paweł Krzysztof Nowak, Tal Linzen, Fei Sha, Kristina Toutanova
NAACL 2022 · Code

Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both?
Peter Shaw, Ming-Wei Chang, Panupong Pasupat, Kristina Toutanova
ACL 2021 · Code

Exploring Unexplored Generalization Challenges for Cross-Database Semantic Parsing
Alane Suhr, Ming-Wei Chang, Peter Shaw, Kenton Lee
ACL 2020 · Code

Generating Logical Forms from Graph Representations of Text and Entities
Peter Shaw, Philip Massey, Angelica Chen, Francesco Piccinno, Yasemin Altun
ACL 2019

Self-Attention with Relative Position Representations
Peter Shaw, Jakob Uszkoreit, Ashish Vaswani
NAACL 2018 · Code

^* indicates equal contribution.

See Google Scholar for a complete list of publications.

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About

My current and recent work includes:

• Gemini post-training - Focusing on tool use and reinforcement learning.
• Foundational machine learning research - Topics related to compositionality, compression, and generalization.
• Computational biology - Neural networks for protein modeling.

Prior to joining Google Research in 2019, I worked on structured query understanding for Google Search, where I led the development and deployment of the first Transformer-based neural networks in Google Search. Before joining Google in 2015, I was the technical lead and manager of the embedded software team at MakerBot, developing 3D printers and scanners. I graduated summa cum laude from Villanova University with a combined Bachelor's and Master's in Electrical Engineering.