Alex Warstadt | DeepAI

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∙ 01/27/2023

Call for Papers – The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus

We present the call for papers for the BabyLM Challenge: Sample-efficien...

0 Alex Warstadt, et al. ∙

∙ 12/21/2022

Reconstruction Probing

We propose reconstruction probing, a new analysis method for contextuali...

0 Najoung Kim, et al. ∙

∙ 09/26/2022

Entailment Semantics Can Be Extracted from an Ideal Language Model

Language models are often trained on text alone, without additional grou...

0 William Merrill, et al. ∙

∙ 08/17/2022

What Artificial Neural Networks Can Tell Us About Human Language Acquisition

Rapid progress in machine learning for natural language processing has t...

14 Alex Warstadt, et al. ∙

∙ 03/12/2022

What Makes Reading Comprehension Questions Difficult?

For a natural language understanding benchmark to be useful in research,...

0 Saku Sugawara, et al. ∙

∙ 09/14/2021

NOPE: A Corpus of Naturally-Occurring Presuppositions in English

Understanding language requires grasping not only the overtly stated con...

0 Alicia Parrish, et al. ∙

∙ 06/01/2021

What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks?

Crowdsourcing is widely used to create data for common natural language ...

0 Nikita Nangia, et al. ∙

∙ 04/15/2021

Does Putting a Linguist in the Loop Improve NLU Data Collection?

Many crowdsourced NLP datasets contain systematic gaps and biases that a...

0 Alicia Parrish, et al. ∙

∙ 01/26/2021

CLiMP: A Benchmark for Chinese Language Model Evaluation

Linguistically informed analyses of language models (LMs) contribute to ...

0 Beilei Xiang, et al. ∙

∙ 11/10/2020

When Do You Need Billions of Words of Pretraining Data?

NLP is currently dominated by general-purpose pretrained language models...

0 Yian Zhang, et al. ∙

∙ 10/11/2020

Learning Which Features Matter: RoBERTa Acquires a Preference for Linguistic Generalizations (Eventually)

One reason pretraining on self-supervised linguistic tasks is effective ...

0 Alex Warstadt, et al. ∙

∙ 07/14/2020

Can neural networks acquire a structural bias from raw linguistic data?

We evaluate whether BERT, a widely used neural network for sentence proc...

0 Alex Warstadt, et al. ∙

∙ 04/07/2020

Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition

Natural language inference (NLI) is an increasingly important task for n...

0 Paloma Jeretič, et al. ∙

∙ 12/02/2019

BLiMP: A Benchmark of Linguistic Minimal Pairs for English

We introduce The Benchmark of Linguistic Minimal Pairs (shortened to BLi...

0 Alex Warstadt, et al. ∙

∙ 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...

0 Alex Warstadt, et al. ∙

∙ 01/11/2019

Grammatical Analysis of Pretrained Sentence Encoders with Acceptability Judgments

Recent pretrained sentence encoders achieve state of the art results on ...

0 Alex Warstadt, et al. ∙

∙ 11/27/2018

Verb Argument Structure Alternations in Word and Sentence Embeddings

Verbs occur in different syntactic environments, or frames. We investiga...

0 Katharina Kann, et al. ∙

∙ 05/31/2018

Neural Network Acceptability Judgments

In this work, we explore the ability of artificial neural networks to ju...

0 Alex Warstadt, et al. ∙

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