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09/16/2023
Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data?
Despite the power of Large Language Models (LLMs) like GPT-4, they still...
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05/23/2023
Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs
Large language models (LLMs) have achieved widespread success on a varie...
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04/17/2023
Tool Learning with Foundation Models
Humans possess an extraordinary ability to create and utilize tools, all...
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02/16/2023
Pretraining Language Models with Human Preferences
Language models (LMs) are pretrained to imitate internet text, including...
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11/22/2022
HyperTuning: Toward Adapting Large Language Models without Back-propagation
Fine-tuning large language models for different tasks can be costly and ...
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10/27/2022
What Language Model to Train if You Have One Million GPU Hours?
The crystallization of modeling methods around the Transformer architect...
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10/19/2022
Two-Turn Debate Doesn't Help Humans Answer Hard Reading Comprehension Questions
The use of language-model-based question-answering systems to aid humans...
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10/12/2022
EleutherAI: Going Beyond "Open Science" to "Science in the Open"
Over the past two years, EleutherAI has established itself as a radicall...
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08/26/2022
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey
We present the results of the NLP Community Metasurvey. Run from May to ...
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08/08/2022
Investigating Efficiently Extending Transformers for Long Input Summarization
While large pretrained Transformer models have proven highly capable at ...
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05/23/2022
SQuALITY: Building a Long-Document Summarization Dataset the Hard Way
Summarization datasets are often assembled either by scraping naturally ...
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04/14/2022
GPT-NeoX-20B: An Open-Source Autoregressive Language Model
We introduce GPT-NeoX-20B, a 20 billion parameter autoregressive languag...
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04/11/2022
Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions
Current QA systems can generate reasonable-sounding yet false answers wi...
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12/16/2021
QuALITY: Question Answering with Long Input Texts, Yes!
To enable building and testing models on long-document comprehension, we...
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11/16/2021
Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair
More capable language models increasingly saturate existing task benchma...
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10/15/2021
BBQ: A Hand-Built Bias Benchmark for Question Answering
It is well documented that NLP models learn social biases present in the...
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09/17/2021
Fine-Tuned Transformers Show Clusters of Similar Representations Across Layers
Despite the success of fine-tuning pretrained language encoders like BER...
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06/01/2021
Comparing Test Sets with Item Response Theory
Recent years have seen numerous NLP datasets introduced to evaluate the ...
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12/31/2020
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Recent work has demonstrated that increased training dataset diversity i...
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10/19/2020
Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability
Saliency maps that identify the most informative regions of an image for...
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09/19/2020
Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms
Breast cancer is the most common cancer in women, and hundreds of thousa...
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05/26/2020
English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too
Intermediate-task training has been shown to substantially improve pretr...
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05/01/2020
Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?
While pretrained models such as BERT have shown large gains across natur...
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03/04/2020
jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models
We introduce jiant, an open source toolkit for conducting multitask and ...
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02/13/2020
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization
Medical images differ from natural images in significantly higher resolu...
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11/27/2019
Do Attention Heads in BERT Track Syntactic Dependencies?
We investigate the extent to which individual attention heads in pretrai...
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09/05/2019
Investigating BERT's Knowledge of Language: Five Analysis Methods with NPIs
Though state-of-the-art sentence representation models can perform tasks...
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08/01/2019
Improving localization-based approaches for breast cancer screening exam classification
We trained and evaluated a localization-based deep CNN for breast cancer...
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07/30/2019
Screening Mammogram Classification with Prior Exams
Radiologists typically compare a patient's most recent breast cancer scr...
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06/07/2019
Globally-Aware Multiple Instance Classifier for Breast Cancer Screening
Deep learning models designed for visual classification tasks on natural...
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03/20/2019
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
We present a deep convolutional neural network for breast cancer screeni...
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11/02/2018
Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks
Pretraining with language modeling and related unsupervised tasks has re...
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09/07/2018