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05/24/2023
Modeling rapid language learning by distilling Bayesian priors into artificial neural networks
Humans can learn languages from remarkably little experience. Developing...
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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...
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08/11/2022
Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages
Machine translation has seen rapid progress with the advent of Transform...
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05/02/2022
Neurocompositional computing: From the Central Paradox of Cognition to a new generation of AI systems
What explains the dramatic progress from 20th-century to 21st-century AI...
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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 ...
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11/24/2020
Picking BERT's Brain: Probing for Linguistic Dependencies in Contextualized Embeddings Using Representational Similarity Analysis
As the name implies, contextualized representations of language are typi...
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06/29/2020
Universal linguistic inductive biases via meta-learning
How do learners acquire languages from the limited data available to the...
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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...
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04/24/2020
Syntactic Data Augmentation Increases Robustness to Inference Heuristics
Pretrained neural models such as BERT, when fine-tuned to perform natura...
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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...
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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...
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05/15/2019
What do you learn from context? Probing for sentence structure in contextualized word representations
Contextualized representation models such as ELMo (Peters et al., 2018a)...
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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...
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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...
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12/28/2018
Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling
Work on the problem of contextualized word representation -- the develop...
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12/20/2018
RNNs Implicitly Implement Tensor Product Representations
Recurrent neural networks (RNNs) can learn continuous vector representat...
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11/29/2018
Non-entailed subsequences as a challenge for natural language inference
Neural network models have shown great success at natural language infer...
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02/25/2018