b'Tal Linzen'

research

∙ 08/10/2023

Do Language Models Refer?

What do language models (LMs) do with language? Everyone agrees that the...

0 Matthew Mandelkern, et al. ∙

research

∙ 06/09/2023

Language Models Can Learn Exceptions to Syntactic Rules

Artificial neural networks can generalize productively to novel contexts...

0 Cara Su-Yi Leong, et al. ∙

research

∙ 05/31/2023

How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases

Accurate syntactic representations are essential for robust generalizati...

0 Aaron Mueller, et al. ∙

research

∙ 01/26/2023

How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech

When acquiring syntax, children consistently choose hierarchical rules o...

0 Aditya Yedetore, et al. ∙

research

∙ 12/21/2022

Uncontrolled Lexical Exposure Leads to Overestimation of Compositional Generalization in Pretrained Models

Human linguistic capacity is often characterized by compositionality and...

0 Najoung Kim, et al. ∙

research

∙ 10/25/2022

Causal Analysis of Syntactic Agreement Neurons in Multilingual Language Models

Structural probing work has found evidence for latent syntactic informat...

0 Aaron Mueller, et al. ∙

research

∙ 10/24/2022

Characterizing Verbatim Short-Term Memory in Neural Language Models

When a language model is trained to predict natural language sequences, ...

0 Kristijan Armeni, et al. ∙

research

∙ 10/21/2022

Syntactic Surprisal From Neural Models Predicts, But Underestimates, Human Processing Difficulty From Syntactic Ambiguities

Humans exhibit garden path effects: When reading sentences that are temp...

0 Suhas Arehalli, et al. ∙

research

∙ 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. ∙

research

∙ 05/06/2022

When a sentence does not introduce a discourse entity, Transformer-based models still sometimes refer to it

Understanding longer narratives or participating in conversations requir...

0 Sebastian Schuster, et al. ∙

research

∙ 03/17/2022

Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models

Relations between words are governed by hierarchical structure rather th...

0 Aaron Mueller, et al. ∙

research

∙ 12/14/2021

Improving Compositional Generalization with Latent Structure and Data Augmentation

Generic unstructured neural networks have been shown to struggle on out-...

6 Linlu Qiu, et al. ∙

research

∙ 11/18/2021

How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN

Current language models can generate high-quality text. Are they simply ...

0 R. Thomas McCoy, et al. ∙

research

∙ 11/09/2021

Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks

Neural network models often generalize poorly to mismatched domains or d...

4 Wang Zhu, et al. ∙

research

∙ 09/16/2021

The Language Model Understood the Prompt was Ambiguous: Probing Syntactic Uncertainty Through Generation

Temporary syntactic ambiguities arise when the beginning of a sentence i...

0 Laura Aina, et al. ∙

research

∙ 09/14/2021

Frequency Effects on Syntactic Rule Learning in Transformers

Pre-trained language models perform well on a variety of linguistic task...

0 Jason Wei, et al. ∙

research

∙ 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. ∙

research

∙ 06/30/2021

The MultiBERTs: BERT Reproductions for Robustness Analysis

Experiments with pretrained models such as BERT are often based on a sin...

0 Thibault Sellam, et al. ∙

research

∙ 06/10/2021

Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models

Targeted syntactic evaluations have demonstrated the ability of language...

0 Matthew Finlayson, et al. ∙

research

∙ 05/14/2021

Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction

When language models process syntactically complex sentences, do they us...

24 Shauli Ravfogel, et al. ∙

research

∙ 04/30/2021

Evaluating Groundedness in Dialogue Systems: The BEGIN Benchmark

Knowledge-grounded dialogue agents are systems designed to conduct a con...

0 Nouha Dziri, et al. ∙

research

∙ 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. ∙

research

∙ 10/12/2020

COGS: A Compositional Generalization Challenge Based on Semantic Interpretation

Natural language is characterized by compositionality: the meaning of a ...

0 Najoung Kim, et al. ∙

research

∙ 06/29/2020

Universal linguistic inductive biases via meta-learning

How do learners acquire languages from the limited data available to the...

0 R. Thomas McCoy, et al. ∙

research

∙ 05/03/2020

How Can We Accelerate Progress Towards Human-like Linguistic Generalization?

This position paper describes and critiques the Pretraining-Agnostic Ide...

0 Tal Linzen, et al. ∙

research

∙ 05/01/2020

Cross-Linguistic Syntactic Evaluation of Word Prediction Models

A range of studies have concluded that neural word prediction models can...

0 Aaron Mueller, et al. ∙

research

∙ 04/30/2020

Representations of Syntax [MASK] Useful: Effects of Constituency and Dependency Structure in Recursive LSTMs

Sequence-based neural networks show significant sensitivity to syntactic...

0 Michael A Lepori, et al. ∙

research

∙ 04/24/2020

Syntactic Data Augmentation Increases Robustness to Inference Heuristics

Pretrained neural models such as BERT, when fine-tuned to perform natura...

0 Junghyun Min, et al. ∙

research

∙ 04/22/2020

Syntactic Structure from Deep Learning

Modern deep neural networks achieve impressive performance in engineerin...

0 Tal Linzen, et al. ∙

research

∙ 01/10/2020

Does syntax need to grow on trees? Sources of hierarchical inductive bias in sequence-to-sequence networks

Learners that are exposed to the same training data might generalize dif...

0 R. Thomas McCoy, et al. ∙

research

∙ 11/07/2019

BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performance

If the same neural architecture is trained multiple times on the same da...

0 R. Thomas McCoy, et al. ∙

research

∙ 10/21/2019

Discovering the Compositional Structure of Vector Representations with Role Learning Networks

Neural networks (NNs) are able to perform tasks that rely on composition...

0 Paul Soulos, et al. ∙

research

∙ 09/23/2019

Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Models

Neural language models (LMs) perform well on tasks that require sensitiv...

0 Grusha Prasad, et al. ∙

research

∙ 08/31/2019

Quantity doesn't buy quality syntax with neural language models

Recurrent neural networks can learn to predict upcoming words remarkably...

0 Marten van Schijndel, et al. ∙

research

∙ 04/25/2019

Probing What Different NLP Tasks Teach Machines about Function Word Comprehension

We introduce a set of nine challenge tasks that test for the understandi...

0 Najoung Kim, et al. ∙

research

∙ 04/05/2019

Analyzing and Interpreting Neural Networks for NLP: A Report on the First BlackboxNLP Workshop

The EMNLP 2018 workshop BlackboxNLP was dedicated to resources and techn...

0 Afra Alishahi, et al. ∙

research

∙ 03/15/2019

Studying the Inductive Biases of RNNs with Synthetic Variations of Natural Languages

How do typological properties such as word order and morphological case ...

0 Shauli Ravfogel, et al. ∙

research

∙ 02/04/2019

Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference

Machine learning systems can often achieve high performance on a test se...

0 R. Thomas McCoy, et al. ∙

research

∙ 01/14/2019

Human few-shot learning of compositional instructions

People learn in fast and flexible ways that have not been emulated by ma...

0 Brenden M. Lake, et al. ∙

research

∙ 12/20/2018

RNNs Implicitly Implement Tensor Product Representations

Recurrent neural networks (RNNs) can learn continuous vector representat...

0 R. Thomas McCoy, et al. ∙

research

∙ 11/29/2018

Non-entailed subsequences as a challenge for natural language inference

Neural network models have shown great success at natural language infer...

0 R. Thomas McCoy, et al. ∙

research

∙ 10/26/2018

Can Entropy Explain Successor Surprisal Effects in Reading?

Human reading behavior is sensitive to surprisal: more predictable words...

0 Marten van Schijndel, et al. ∙

research

∙ 09/11/2018

What can linguistics and deep learning contribute to each other?

Joe Pater's target article calls for greater interaction between neural ...

0 Tal Linzen, et al. ∙

research

∙ 08/29/2018

A Neural Model of Adaptation in Reading

It has been argued that humans rapidly adapt their lexical and syntactic...

0 Marten van Schijndel, et al. ∙

research

∙ 08/27/2018

Targeted Syntactic Evaluation of Language Models

We present a dataset for evaluating the grammaticality of the prediction...

0 Rebecca Marvin, et al. ∙

research

∙ 07/18/2018

Distinct patterns of syntactic agreement errors in recurrent networks and humans

Determining the correct form of a verb in context requires an understand...

0 Tal Linzen, et al. ∙

research

∙ 03/29/2018

Colorless green recurrent networks dream hierarchically

Recurrent neural networks (RNNs) have achieved impressive results in a v...

0 Kristina Gulordava, et al. ∙

research

∙ 02/25/2018

Revisiting the poverty of the stimulus: hierarchical generalization without a hierarchical bias in recurrent neural networks

Syntactic rules in human language usually refer to the hierarchical stru...

0 R. Thomas McCoy, et al. ∙

research

∙ 11/17/2017

Phonological (un)certainty weights lexical activation

Spoken word recognition involves at least two basic computations. First ...

0 Laura Gwilliams, et al. ∙

research

∙ 06/12/2017

Exploring the Syntactic Abilities of RNNs with Multi-task Learning

Recent work has explored the syntactic abilities of RNNs using the subje...

0 Emile Enguehard, et al. ∙

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