Jason Phang

According to our database1, Jason Phang authored at least 27 papers between 2018 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2022
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey.
CoRR, 2022

Investigating Efficiently Extending Transformers for Long Input Summarization.
CoRR, 2022

SQuALITY: Building a Long-Document Summarization Dataset the Hard Way.
CoRR, 2022

GPT-NeoX-20B: An Open-Source Autoregressive Language Model.
CoRR, 2022

Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions.
CoRR, 2022

QuALITY: Question Answering with Long Input Texts, Yes!
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

BBQ: A hand-built bias benchmark for question answering.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization.
Medical Image Anal., 2021

Reducing False-Positive Biopsies using Deep Neural Networks that Utilize both Local and Global Image Context of Screening Mammograms.
J. Digit. Imaging, 2021

Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair.
CoRR, 2021

The Pile: An 800GB Dataset of Diverse Text for Language Modeling.
CoRR, 2021

Fine-Tuned Transformers Show Clusters of Similar Representations Across Layers.
Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2021

Comparing Test Sets with Item Response Theory.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.
IEEE Trans. Medical Imaging, 2020

Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability.
CoRR, 2020

Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms.
CoRR, 2020

Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?
CoRR, 2020

English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too.
Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, 2020

jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 2020

Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Do Attention Heads in BERT Track Syntactic Dependencies?
CoRR, 2019

Improving localization-based approaches for breast cancer screening exam classification.
CoRR, 2019

Screening Mammogram Classification with Prior Exams.
CoRR, 2019

Globally-Aware Multiple Instance Classifier for Breast Cancer Screening.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Investigating BERT's Knowledge of Language: Five Analysis Methods with NPIs.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018
Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks.
CoRR, 2018

Unsupervised Sentence Compression using Denoising Auto-Encoders.
Proceedings of the 22nd Conference on Computational Natural Language Learning, 2018


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