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nlp:structured_prediction

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nlp:structured_prediction [2021/04/01 10:17] – [Recent Papers] jmflanignlp:structured_prediction [2023/06/15 07:36] (current) – external edit 127.0.0.1
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   * [[https://arxiv.org/pdf/1711.04956v5.pdf|Edunov et al 2017 - Classical Structured Prediction Losses for Sequence to Sequence Learning]]  Uses a sample (i.e. beam) size of 16 for the MT experiments.  See section 6.5 and Table 2.   * [[https://arxiv.org/pdf/1711.04956v5.pdf|Edunov et al 2017 - Classical Structured Prediction Losses for Sequence to Sequence Learning]]  Uses a sample (i.e. beam) size of 16 for the MT experiments.  See section 6.5 and Table 2.
   *  [[https://arxiv.org/pdf/1807.01745.pdf|Gómez-Rodríguez et al 2018 - Global Transition-based Non-projective Dependency Parsing]]   *  [[https://arxiv.org/pdf/1807.01745.pdf|Gómez-Rodríguez et al 2018 - Global Transition-based Non-projective Dependency Parsing]]
-  * [[https://www.aclweb.org/anthology/P18-1173.pdf|Peng et al 2018 - Backpropagating through Structured Argmax using a SPIGOT]] (see also [[ml:Optimization in Deep Learning#Backpropagating Through Discontinuities]]+  * [[https://www.aclweb.org/anthology/P18-1173.pdf|Peng et al 2018 - Backpropagating through Structured Argmax using a SPIGOT]] (see also [[ml:Optimization in Deep Learning#Backpropagating Through Discontinuities]])
   * [[https://arxiv.org/pdf/1906.07880.pdf|Wang et al 2018 - Second-Order Semantic Dependency Parsing with End-to-End Neural Networks]]   * [[https://arxiv.org/pdf/1906.07880.pdf|Wang et al 2018 - Second-Order Semantic Dependency Parsing with End-to-End Neural Networks]]
   * [[https://www.aclweb.org/anthology/K18-1001.pdf|Thai et al 2018 - Embedded-State Latent Conditional Random Fields for Sequence Labeling]]   * [[https://www.aclweb.org/anthology/K18-1001.pdf|Thai et al 2018 - Embedded-State Latent Conditional Random Fields for Sequence Labeling]]
   * [[https://par.nsf.gov/servlets/purl/10145797|Ma et al 2019 - Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning]]   * [[https://par.nsf.gov/servlets/purl/10145797|Ma et al 2019 - Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning]]
   * **[[http://proceedings.mlr.press/v97/collobert19a/collobert19a.pdf|Collobert 2019 - A Fully Differentiable Beam Search Decoder]]**   * **[[http://proceedings.mlr.press/v97/collobert19a/collobert19a.pdf|Collobert 2019 - A Fully Differentiable Beam Search Decoder]]**
-  * [[https://www.aclweb.org/anthology/D19-1099.pdf|2019 - Semantic Role Labeling with Iterative Structure Refinement]] Good related work section+  * [[https://www.aclweb.org/anthology/N19-1171.pdf|Goyal et al 2019 - An Empirical Investigation of Global and Local Normalization for Recurrent Neural Sequence Models Using a Continuous Relaxation to Beam Search]]
   * [[https://www.aclweb.org/anthology/N19-1335.pdf|Tu & Gimple 2019 - Benchmarking Approximate Inference Methods for Neural Structured Prediction]]   * [[https://www.aclweb.org/anthology/N19-1335.pdf|Tu & Gimple 2019 - Benchmarking Approximate Inference Methods for Neural Structured Prediction]]
 +  * [[https://www.aclweb.org/anthology/D19-1099.pdf|2019 - Semantic Role Labeling with Iterative Structure Refinement]] Good related work section
   * [[https://arxiv.org/pdf/2005.00975.pdf|Zhang et al 2020 - Efficient Second-Order TreeCRF for Neural Dependency Parsing]]   * [[https://arxiv.org/pdf/2005.00975.pdf|Zhang et al 2020 - Efficient Second-Order TreeCRF for Neural Dependency Parsing]]
   * [[https://www.aclweb.org/anthology/2020.acl-demos.38.pdf|Rush 2020 - Torch-Struct: Deep Structured Prediction Library]]   * [[https://www.aclweb.org/anthology/2020.acl-demos.38.pdf|Rush 2020 - Torch-Struct: Deep Structured Prediction Library]]
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 ==== Conferences and Workshops ==== ==== Conferences and Workshops ====
   * [[https://www.aclweb.org/anthology/2020.spnlp-1.0.pdf|4th Workshop on Structured Prediction for NLP]]   * [[https://www.aclweb.org/anthology/2020.spnlp-1.0.pdf|4th Workshop on Structured Prediction for NLP]]
 +
 +==== Courses and Tutorials ====
 +  * Structured Prediction for Language and Other Discrete Data (SPFLODD) course at CMU: [[http://demo.clab.cs.cmu.edu/fa2015-11763/|2015]] [[https://sites.google.com/site/spflodd/|2014]]
  
 ===== Related Pages ===== ===== Related Pages =====
   * [[Structured Prediction Energy Networks]]   * [[Structured Prediction Energy Networks]]
   * [[Label Bias Problem]]   * [[Label Bias Problem]]
nlp/structured_prediction.1617272251.txt.gz · Last modified: 2023/06/15 07:36 (external edit)
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