A survey on non-autoregressive generation for neural machine translation and beyond
Non-autoregressive (NAR) generation, which is first proposed in neural machine translation
(NMT) to speed up inference, has attracted much attention in both machine learning and …
(NMT) to speed up inference, has attracted much attention in both machine learning and …
Benchclamp: A benchmark for evaluating language models on syntactic and semantic parsing
Recent work has shown that generation from a prompted or fine-tuned language model can
perform well at semantic parsing when the output is constrained to be a valid semantic …
perform well at semantic parsing when the output is constrained to be a valid semantic …
Transition-based parsing with stack-transformers
Modeling the parser state is key to good performance in transition-based parsing. Recurrent
Neural Networks considerably improved the performance of transition-based systems by …
Neural Networks considerably improved the performance of transition-based systems by …
Understanding models understanding language
A Søgaard - Synthese, 2022 - Springer
Abstract Landgrebe and Smith (Synthese 198 (March): 2061–2081, 2021) present an
unflattering diagnosis of recent advances in what they call language-centric artificial …
unflattering diagnosis of recent advances in what they call language-centric artificial …
The unstoppable rise of computational linguistics in deep learning
J Henderson - arXiv preprint arXiv:2005.06420, 2020 - arxiv.org
In this paper, we trace the history of neural networks applied to natural language
understanding tasks, and identify key contributions which the nature of language has made …
understanding tasks, and identify key contributions which the nature of language has made …
Dependency parsing as mrc-based span-span prediction
Higher-order methods for dependency parsing can partially but not fully address the issue
that edges in dependency trees should be constructed at the text span/subtree level rather …
that edges in dependency trees should be constructed at the text span/subtree level rather …
Dependency parsing via sequence generation
Dependency parsing aims to extract syntactic dependency structure or semantic
dependency structure for sentences. Existing methods for dependency parsing include …
dependency structure for sentences. Existing methods for dependency parsing include …
Graph refinement for coreference resolution
L Miculicich, J Henderson - arXiv preprint arXiv:2203.16574, 2022 - arxiv.org
The state-of-the-art models for coreference resolution are based on independent mention
pair-wise decisions. We propose a modelling approach that learns coreference at the …
pair-wise decisions. We propose a modelling approach that learns coreference at the …
Graph-to-graph transformer for transition-based dependency parsing
A Mohammadshahi, J Henderson - arXiv preprint arXiv:1911.03561, 2019 - arxiv.org
We propose the Graph2Graph Transformer architecture for conditioning on and predicting
arbitrary graphs, and apply it to the challenging task of transition-based dependency …
arbitrary graphs, and apply it to the challenging task of transition-based dependency …
Enhancing structure-aware encoder with extremely limited data for graph-based dependency parsing
Dependency parsing is an important fundamental natural language processing task which
analyzes the syntactic structure of an input sentence by illustrating the syntactic relations …
analyzes the syntactic structure of an input sentence by illustrating the syntactic relations …