Analysis methods in neural language processing: A survey
Y Belinkov, J Glass - … of the Association for Computational Linguistics, 2019 - direct.mit.edu
The field of natural language processing has seen impressive progress in recent years, with
neural network models replacing many of the traditional systems. A plethora of new models …
neural network models replacing many of the traditional systems. A plethora of new models …
Unsupervised recurrent neural network grammars
Recurrent neural network grammars (RNNG) are generative models of language which
jointly model syntax and surface structure by incrementally generating a syntax tree and …
jointly model syntax and surface structure by incrementally generating a syntax tree and …
Recursion in recursion: Two-level nested recursion for length generalization with scalability
J Ray Chowdhury, C Caragea - Advances in Neural …, 2024 - proceedings.neurips.cc
Abstract Binary Balanced Tree Recursive Neural Networks (BBT-RvNNs) enforce sequence
composition according to a preset balanced binary tree structure. Thus, their non-linear …
composition according to a preset balanced binary tree structure. Thus, their non-linear …
Visually grounded neural syntax acquisition
We present the Visually Grounded Neural Syntax Learner (VG-NSL), an approach for
learning syntactic representations and structures without any explicit supervision. The model …
learning syntactic representations and structures without any explicit supervision. The model …
Jointly learning sentence embeddings and syntax with unsupervised tree-lstms
We present two studies on neural network architectures that learn to represent sentences by
composing their words according to automatically induced binary trees, without ever being …
composing their words according to automatically induced binary trees, without ever being …
Cooperative learning of disjoint syntax and semantics
There has been considerable attention devoted to models that learn to jointly infer an
expression's syntactic structure and its semantics. Yet,\citet {NangiaB18} has recently shown …
expression's syntactic structure and its semantics. Yet,\citet {NangiaB18} has recently shown …
Grammar-based grounded lexicon learning
Abstract We present Grammar-Based Grounded Language Learning (G2L2), a lexicalist
approach toward learning a compositional and grounded meaning representation of …
approach toward learning a compositional and grounded meaning representation of …
Beam tree recursive cells
JR Chowdhury, C Caragea - International Conference on …, 2023 - proceedings.mlr.press
Abstract We propose Beam Tree Recursive Cell (BT-Cell)-a backpropagation-friendly
framework to extend Recursive Neural Networks (RvNNs) with beam search for latent …
framework to extend Recursive Neural Networks (RvNNs) with beam search for latent …
What are the goals of distributional semantics?
G Emerson - arXiv preprint arXiv:2005.02982, 2020 - arxiv.org
Distributional semantic models have become a mainstay in NLP, providing useful features
for downstream tasks. However, assessing long-term progress requires explicit long-term …
for downstream tasks. However, assessing long-term progress requires explicit long-term …
Efficient beam tree recursion
JR Chowdhury, C Caragea - arXiv preprint arXiv:2307.10779, 2023 - arxiv.org
Beam Tree Recursive Neural Network (BT-RvNN) was recently proposed as a simple
extension of Gumbel Tree RvNN and it was shown to achieve state-of-the-art length …
extension of Gumbel Tree RvNN and it was shown to achieve state-of-the-art length …