125 citations · 584 across the 45 of their papers we have counts for
8 papers · 1 filter
COGS: A Compositional Generalization Challenge Based on Semantic Interpretation
Najoung Kim, Tal Linzen
Natural language is characterized by compositionality: the meaning of a complex expression is constructed from the meanings of its constituent parts. To facilitate the evaluation o…
Universal linguistic inductive biases via meta-learning
R. Thomas McCoy, Erin Grant, Paul Smolensky +2
How do learners acquire languages from the limited data available to them? This process must involve some inductive biases - factors that affect how a learner generalizes - but it…
Cross-Linguistic Syntactic Evaluation of Word Prediction Models
Aaron Mueller, Garrett Nicolai, Panayiota Petrou-Zeniou +2
A range of studies have concluded that neural word prediction models can distinguish grammatical from ungrammatical sentences with high accuracy. However, these studies are based p…
How Can We Accelerate Progress Towards Human-like Linguistic Generalization?
Tal Linzen
This position paper describes and critiques the Pretraining-Agnostic Identically Distributed (PAID) evaluation paradigm, which has become a central tool for measuring progress in n…
Representations of Syntax [MASK] Useful: Effects of Constituency and Dependency Structure in Recursive LSTMs
Michael A. Lepori, Tal Linzen, R. Thomas McCoy
Sequence-based neural networks show significant sensitivity to syntactic structure, but they still perform less well on syntactic tasks than tree-based networks. Such tree-based ne…
Syntactic Data Augmentation Increases Robustness to Inference Heuristics
Junghyun Min, R. Thomas McCoy, Dipanjan Das +2
Pretrained neural models such as BERT, when fine-tuned to perform natural language inference (NLI), often show high accuracy on standard datasets, but display a surprising lack of…
Syntactic Structure from Deep Learning
Tal Linzen, Marco Baroni
Modern deep neural networks achieve impressive performance in engineering applications that require extensive linguistic skills, such as machine translation. This success has spark…
Does syntax need to grow on trees? Sources of hierarchical inductive bias in sequence-to-sequence networks
R. Thomas McCoy, Robert Frank, Tal Linzen
Learners that are exposed to the same training data might generalize differently due to differing inductive biases. In neural network models, inductive biases could in theory arise…