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12/20/2022
BUMP: A Benchmark of Unfaithful Minimal Pairs for Meta-Evaluation of Faithfulness Metrics
The proliferation of automatic faithfulness metrics for summarization ha...
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10/19/2022
Continued Pretraining for Better Zero- and Few-Shot Promptability
Recently introduced language model prompting methods can achieve high ac...
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02/15/2022
Impact of Pretraining Term Frequencies on Few-Shot Reasoning
Pretrained Language Models (LMs) have demonstrated ability to perform nu...
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12/16/2021
FRUIT: Faithfully Reflecting Updated Information in Text
Textual knowledge bases such as Wikipedia require considerable effort to...
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06/24/2021
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
Prompting language models (LMs) with training examples and task descript...
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10/29/2020
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
The remarkable success of pretrained language models has motivated the s...
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10/06/2020
Easy, Reproducible and Quality-Controlled Data Collection with Crowdaq
High-quality and large-scale data are key to success for AI systems. How...
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02/16/2020
Active Bayesian Assessment for Black-Box Classifiers
Recent advances in machine learning have led to increased deployment of ...
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09/09/2019
Knowledge Enhanced Contextual Word Representations
Contextual word representations, typically trained on unstructured, unla...
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04/05/2019
PoMo: Generating Entity-Specific Post-Modifiers in Context
We introduce entity post-modifier generation as an instance of a collabo...
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11/29/2017