Sparsemap: Differentiable sparse structured inference
Structured prediction requires searching over a combinatorial number of structures. To
tackle it, we introduce SparseMAP, a new method for sparse structured inference, together …
tackle it, we introduce SparseMAP, a new method for sparse structured inference, together …
Discrete latent structure in neural networks
Many types of data from fields including natural language processing, computer vision, and
bioinformatics, are well represented by discrete, compositional structures such as trees …
bioinformatics, are well represented by discrete, compositional structures such as trees …
Depth-bounding is effective: Improvements and evaluation of unsupervised PCFG induction
There have been several recent attempts to improve the accuracy of grammar induction
systems by bounding the recursive complexity of the induction model (Ponvert et al., 2011; …
systems by bounding the recursive complexity of the induction model (Ponvert et al., 2011; …
Bayesian learning for neural dependency parsing
While neural dependency parsers provide state-of-the-art accuracy for several languages,
they still rely on large amounts of costly labeled training data. We demonstrate that in the …
they still rely on large amounts of costly labeled training data. We demonstrate that in the …
Training for Gibbs sampling on conditional random fields with neural scoring factors
S Gao, MR Gormley - Proceedings of the 2020 Conference on …, 2020 - aclanthology.org
Most recent improvements in NLP come from changes to the neural network architectures
modeling the text input. Yet, state-of-the-art models often rely on simple approaches to …
modeling the text input. Yet, state-of-the-art models often rely on simple approaches to …
Efficient Sampling of Dependency Structures
Probabilistic distributions over spanning trees in directed graphs are a fundamental model of
dependency structure in natural language processing, syntactic dependency trees. In NLP …
dependency structure in natural language processing, syntactic dependency trees. In NLP …
Query-focused sentence compression in linear time
A Handler, B O'Connor - arxiv preprint arxiv:1904.09051, 2019 - arxiv.org
Search applications often display shortened sentences which must contain certain query
terms and must fit within the space constraints of a user interface. This work introduces a …
terms and must fit within the space constraints of a user interface. This work introduces a …
A hitchhiker's guide to efficient non-projective dependency parsing
R Zmigrod - 2022 - repository.cam.ac.uk
Dependency parsing has played a pivotal role in NLP over the last few decades, and non-
projective, graph-based dependency parsers have become a dominant approach for this …
projective, graph-based dependency parsers have become a dominant approach for this …
Social Measurement and Causal Inference with Text
KA Keith - 2021 - scholarworks.umass.edu
The digital age has dramatically increased access to large-scale collections of digitized text
documents. These corpora include, for example, digital traces from social media, decades of …
documents. These corpora include, for example, digital traces from social media, decades of …
Natural Language Processing for Lexical Corpus Analysis
AK Handler - 2021 - scholarworks.umass.edu
People have been analyzing documents by reading keywords in context for centuries.
Traditional approaches like paper concordances or digital keyword-in-context viewers …
Traditional approaches like paper concordances or digital keyword-in-context viewers …