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--- nlp:neurosymbolic_methods [2024/12/18 00:27] – [Papers] jmflanig
+++ nlp:neurosymbolic_methods [2025/08/30 00:35] (current) – [Papers] jmflanig
@@ Line 2: / Line 2: @@
 ===== Overviews =====
   * See related work (section 2) of  [[https://www.aclweb.org/anthology/2020.emnlp-main.453.pdf|Wu 2020]]
+  * [[https://arxiv.org/pdf/2012.05876|d'Avila Garcez & Lamb 2020 - Neurosymbolic AI: The 3rd Wave]]
   * [[https://arxiv.org/pdf/2010.05446.pdf|Zhang et al 2020 - Neural, Symbolic and Neural-Symbolic Reasoning on Knowledge Graphs]]
+  * [[https://arxiv.org/pdf/2305.00813|Sheth et al 2023 - Neurosymbolic AI - Why, What, and How]]
+  * [[https://arxiv.org/pdf/2501.05435|Colelough & Regli 2025 - Neuro-Symbolic AI in 2024: A Systematic Review]]
+  * **Tutorials**
+    * [[https://ns4nlp-coling.github.io/|NS4NLP: Neuro-Symbolic Modeling for NLP - COLING 2022 Tutorial]]
 ===== Papers =====
@@ Line 20: / Line 25: @@
   * [[https://arxiv.org/pdf/2211.11559|Gupta & Kembhavi 2022 - Visual Programming: Compositional visual reasoning without training]]
   * [[https://arxiv.org/pdf/2305.12744|Pan et al 2023 - Fact-Checking Complex Claims with Program-Guided Reasoning]]
+  * [[https://arxiv.org/pdf/2305.12295|Pan et al 2023 - Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning]]
+  * [[https://arxiv.org/pdf/2310.05253|Wang & Shu 2023 - Explainable Claim Verification via Knowledge-Grounded Reasoning with
+Large Language Models]]
   * [[https://arxiv.org/pdf/2310.16035.pdf|Hsu et al 2023 - What’s Left? Concept Grounding with Logic-Enhanced Foundation Models]]
+  * **[[https://arxiv.org/pdf/2506.04592|Liu et al 2025 - Safe: Enhancing Mathematical Reasoning in Large Language Models via Retrospective Step-aware Formal Verification]]**
 ===== People =====