Peter Shaw
Peter Shaw
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Cited by
Self-Attention with Relative Position Representations
P Shaw, J Uszkoreit, A Vaswani
arXiv preprint arXiv:1803.02155, 2018
Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both?
P Shaw, MW Chang, P Pasupat, K Toutanova
arXiv preprint arXiv:2010.12725, 2020
Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding
K Lee, M Joshi, I Turc, H Hu, F Liu, J Eisenschlos, U Khandelwal, P Shaw, ...
arXiv preprint arXiv:2210.03347, 2022
Exploring Unexplored Generalization Challenges for Cross-Database Semantic Parsing
A Suhr, MW Chang, P Shaw, K Lee
Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020
Improving Compositional Generalization with Latent Structure and Data Augmentation
L Qiu, P Shaw, P Pasupat, PK Nowak, T Linzen, F Sha, K Toutanova
arXiv preprint arXiv:2112.07610, 2021
Unlocking Compositional Generalization in Pre-trained Models Using Intermediate Representations
J Herzig, P Shaw, MW Chang, K Guu, P Pasupat, Y Zhang
arXiv preprint arXiv:2104.07478, 2021
Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing
L Qiu, P Shaw, P Pasupat, T Shi, J Herzig, E Pitler, F Sha, K Toutanova
arXiv preprint arXiv:2205.12253, 2022
Generating Logical Forms from Graph Representations of Text and Entities
P Shaw, P Massey, A Chen, F Piccinno, Y Altun
arXiv preprint arXiv:1905.08407, 2019
Answering Conversational Questions on Structured Data without Logical Forms
T Müller, F Piccinno, M Nicosia, P Shaw, Y Altun
arXiv preprint arXiv:1908.11787, 2019
From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces
P Shaw, M Joshi, J Cohan, J Berant, P Pasupat, H Hu, U Khandelwal, ...
arXiv preprint arXiv:2306.00245, 2023
Systematic Generalization on gSCAN: What is Nearly Solved and What is Next?
L Qiu, H Hu, B Zhang, P Shaw, F Sha
arXiv preprint arXiv:2109.12243, 2021
Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking
J Eisenstein, C Nagpal, A Agarwal, A Beirami, A D'Amour, DJ Dvijotham, ...
arXiv preprint arXiv:2312.09244, 2023
Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing
Y Zemlyanskiy, M de Jong, J Ainslie, P Pasupat, P Shaw, L Qiu, ...
arXiv preprint arXiv:2209.14899, 2022
QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations
C Malaviya, P Shaw, MW Chang, K Lee, K Toutanova
arXiv preprint arXiv:2305.11694, 2023
Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks
W Zhu, P Shaw, T Linzen, F Sha
arXiv preprint arXiv:2111.05013, 2021
Visually Grounded Concept Composition
B Zhang, H Hu, L Qiu, P Shaw, F Sha
arXiv preprint arXiv:2109.14115, 2021
Robust Preference Optimization through Reward Model Distillation
A Fisch, J Eisenstein, V Zayats, A Agarwal, A Beirami, C Nagpal, P Shaw, ...
arXiv preprint arXiv:2405.19316, 2024
Graph-Based Decoding for Task Oriented Semantic Parsing
JR Cole, N Jiang, P Pasupat, L He, P Shaw
arXiv preprint arXiv:2109.04587, 2021
BAGEL: Bootstrapping Agents by Guiding Exploration with Language
S Murty, C Manning, P Shaw, M Joshi, K Lee
arXiv preprint arXiv:2403.08140, 2024
ProtEx: A Retrieval-Augmented Approach for Protein Function Prediction
P Shaw, B Gurram, D Belanger, A Gane, ML Bileschi, LJ Colwell, ...
bioRxiv, 2024.05. 30.596539, 2024
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