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08/07/2023
Simple synthetic data reduces sycophancy in large language models
Sycophancy is an undesirable behavior where models tailor their response...
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05/15/2023
Symbol tuning improves in-context learning in language models
We present symbol tuning - finetuning language models on in-context inpu...
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03/07/2023
Larger language models do in-context learning differently
We study how in-context learning (ICL) in language models is affected by...
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01/28/2022
Calibrating Histopathology Image Classifiers using Label Smoothing
The classification of histopathology images fundamentally differs from t...
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01/29/2021
A Petri Dish for Histopathology Image Analysis
With the rise of deep learning, there has been increased interest in usi...
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09/29/2020
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
Applying curriculum learning requires both a range of difficulty in data...
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08/25/2020
Adapting Security Warnings to Counter Online Disinformation
Online platforms are using warning messages to counter disinformation, b...
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06/04/2020
NewB: 200,000+ Sentences for Political Bias Detection
We present the Newspaper Bias Dataset (NewB), a text corpus of more than...
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05/26/2020
What Are People Asking About COVID-19? A Question Classification Dataset
We present COVID-Q, a set of 1,690 questions about COVID-19 from 13 sour...
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04/27/2020
Difficulty Translation in Histopathology Images
The unique nature of histopathology images opens the door to domain-spec...
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10/13/2019