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--- nlp:compositional_generalization [2023/05/15 05:13] – [Overviews] jmflanig
+++ nlp:compositional_generalization [2023/07/07 18:21] (current) – [Papers using Curriculum Learning] jmflanig
@@ Line 2: / Line 2: @@
 ===== Overviews =====
-  * [[https://arxiv.org/pdf/2302.01067.pdf|Lin et al 2023 - A Survey on Compositional Generalization in Applications]] Not an NLP paper, and not very comprehensive.  Missing a bunch of NLP work.
+  * [[https://arxiv.org/pdf/2302.01067.pdf|Lin et al 2023 - A Survey on Compositional Generalization in Applications]] Not an NLP paper, and not very comprehensive.  WARNING: Missing a bunch of NLP work.
 ===== Papers =====
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   * [[https://arxiv.org/pdf/2009.06040.pdf|Herzig & Berant 2020 - Span-based Semantic Parsing for Compositional Generalization]]
   * [[https://arxiv.org/pdf/2010.12725.pdf|Shaw et al 2020 - Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both?]] [[https://github.com/google-research/language/tree/master/language/nqg|Code and data]] Introduces TMCD split method
-  * **[[https://arxiv.org/pdf/2108.12284.pdf|Csordás et al 2021 - The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers]]**
+  * Improving Transformers for COG:
+    * **[[https://arxiv.org/pdf/2108.12284.pdf|Csordás et al 2021 - The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers]]**
+    * [[https://arxiv.org/pdf/2108.04378.pdf|Ontañón et al 2021 - Making Transformers Solve Compositional Tasks]]
 ==== Papers using Curriculum Learning ====
   * [[https://arxiv.org/pdf/2006.10627.pdf|2020 - Compositional Generalization by Learning Analytical Expressions]]
+==== Prompting and Language Models ====
+  * [[https://arxiv.org/pdf/2209.15003.pdf|Drozdov 2022 - Compositional Semantic Parsing with Large Language Models]]
+==== COG in Machine Translation ====
+  * [[https://arxiv.org/pdf/2210.06709.pdf|Yin et al 2022 - Categorizing Semantic Representations for Neural Machine Translation]]
 ==== Non-NLP Papers ====
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     * [[https://yale-lily.github.io/spider|Spider dataset]] [[https://arxiv.org/pdf/1809.08887.pdf|paper]]
   * CFQ dataset [[https://arxiv.org/pdf/1912.09713.pdf|paper]]
+  * PCFG dataset [[https://arxiv.org/pdf/1908.08351.pdf|paper]] (A string edit operation composition benchmark)
   * M-PCFGSET dataset [[https://eliabruni.github.io/publications/hupkes2019compositionality.pdf|paper]]
   * Question Answering