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--- nlp:wfsa [2020/10/29 07:23] – [Recent Developments] jmflanig
+++ nlp:wfsa [2023/06/15 07:36] (current) – external edit 127.0.0.1
@@ Line 2: / Line 2: @@
 Weighted FSAs are the weighted generalizations of FSAs and FSTs.
-===== Key Papers ====
+===== Key Papers =====
+  * [[https://repository.upenn.edu/cgi/viewcontent.cgi?article=1010&context=cis_papers|Mohri et al 2001 - Weighted Finite-State Transducers in Speech Recognition]]
+  * [[https://www.aclweb.org/anthology/P02-1001.pdf|Eisner 2002 - Parameter Estimation for Probabilistic Finite-State Transducers]]
+===== More Papers =====
+  * [[https://www.aclweb.org/anthology/D08-1113.pdf|Dreyer et al 2008 - Latent-Variable Modeling of String Transductions with Finite-State Methods]]
+  * [[https://www.aclweb.org/anthology/D09-1011.pdf|Dreyer et al 2009 - Graphical Models over Multiple Strings]]
-===== Recent Developments ====
+===== Recent Developments =====
+  * [[https://www.aclweb.org/anthology/N16-1076.pdf|Rastogi et al 2016 - Weighting Finite-State Transductions With Neural Context]]
   * [[paper:Schwartz 2018 - SoPa Bridging CNNs, RNNs, and Weighted Finite-State Machines]]
+  * [[https://www.aclweb.org/anthology/N19-1024.pdf|Lin et al 2019 - Neural Finite State Transducers: Beyond Rational Relations]]
   * [[https://arxiv.org/pdf/2010.01003.pdf|Hannun et al 2020 - Differentiable Weighted Finite-State Transducers]]
   * [[https://arxiv.org/pdf/2004.00478.pdf|Marzouk et al 2020 - Distance and Equivalence between Finite State Machines and Recurrent Neural Networks: Computational results]]
+  * [[https://www.aclweb.org/anthology/2020.emnlp-main.258.pdf|Jiang et al 2020 - Cold-Start and Interpretability: Turning Regular Expressions into Trainable Recurrent Neural Networks]]
+  * [[https://arxiv.org/pdf/2301.06862.pdf|Svete et al 2023 - Algorithms for Acyclic Weighted Finite-State Automata with Failure Arcs]]
+===== Converting RNNs to WFSAs =====
+  * [[https://arxiv.org/pdf/1910.13895.pdf|Weiss et al 2019 - Learning Deterministic Weighted Automata with Queries and Counterexamples]]
+===== Related Pages =====
+  * [[RNN|Recurrent Neural Networks]]