Compositional generalization in semantic parsing with pretrained transformers

30 September 2021

Papers citing "Compositional generalization in semantic parsing with pretrained transformers"

11 / 11 papers shown

Title
VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance Katherine Crowson Stella Biderman Daniel Kornis Dashiell Stander Eric Hallahan Louis Castricato Edward Raff CLIP 96 375 0 18 Apr 2022
Does Pretraining for Summarization Require Knowledge Transfer? Kundan Krishna Jeffrey P. Bigham Zachary Chase Lipton 62 39 0 10 Sep 2021
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation Yue Wang Weishi Wang Shafiq Joty Guosheng Lin 271 1,532 0 02 Sep 2021
Learning to See by Looking at Noise Manel Baradad Jonas Wulff Tongzhou Wang Phillip Isola Antonio Torralba 59 91 0 10 Jun 2021
Are Pre-trained Convolutions Better than Pre-trained Transformers? Yi Tay Mostafa Dehghani J. Gupta Dara Bahri V. Aribandi Zhen Qin Donald Metzler AI4CE 35 49 0 07 May 2021
Pretrained Transformers as Universal Computation Engines Kevin Lu Aditya Grover Pieter Abbeel Igor Mordatch 42 220 0 09 Mar 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 319 4,873 0 24 Feb 2021
Pre-Training a Language Model Without Human Language Cheng-Han Chiang Hung-yi Lee 29 13 0 22 Dec 2020
COGS: A Compositional Generalization Challenge Based on Semantic Interpretation Najoung Kim Tal Linzen CoGe 39 276 0 12 Oct 2020
Pretrained Transformers Improve Out-of-Distribution Robustness Dan Hendrycks Xiaoyuan Liu Eric Wallace Adam Dziedzic R. Krishnan D. Song OOD 120 430 0 13 Apr 2020
Self-training with Noisy Student improves ImageNet classification Qizhe Xie Minh-Thang Luong Eduard H. Hovy Quoc V. Le NoLa 213 2,375 0 11 Nov 2019