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We present <jats:inline-formula>\n              <jats:alternatives>\n                <jats:tex-math>$$_\\text {CAV25}$$<\/jats:tex-math>\n                <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:msub>\n                    <mml:mrow\/>\n                    <mml:mrow>\n                      <mml:mi>CAV<\/mml:mi>\n                      <mml:mn>25<\/mml:mn>\n                    <\/mml:mrow>\n                  <\/mml:msub>\n                <\/mml:math>\n              <\/jats:alternatives>\n            <\/jats:inline-formula>, a high-performance DNN verification tool that uses the DPLL(T) framework and supports a wide-range of network architectures and activation functions. Since its debut in VNN-COMP\u201923, in which it achieved the New Participant Award and ranked 4th overall, <jats:inline-formula>\n              <jats:alternatives>\n                <jats:tex-math>$$_\\text {CAV25}$$<\/jats:tex-math>\n                <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:msub>\n                    <mml:mrow\/>\n                    <mml:mrow>\n                      <mml:mi>CAV<\/mml:mi>\n                      <mml:mn>25<\/mml:mn>\n                    <\/mml:mrow>\n                  <\/mml:msub>\n                <\/mml:math>\n              <\/jats:alternatives>\n            <\/jats:inline-formula> has advanced significantly, achieving second place in VNN-COMP\u201924. This paper presents and evaluates the latest development of <jats:inline-formula>\n              <jats:alternatives>\n                <jats:tex-math>$$_\\text {CAV25}$$<\/jats:tex-math>\n                <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:msub>\n                    <mml:mrow\/>\n                    <mml:mrow>\n                      <mml:mi>CAV<\/mml:mi>\n                      <mml:mn>25<\/mml:mn>\n                    <\/mml:mrow>\n                  <\/mml:msub>\n                <\/mml:math>\n              <\/jats:alternatives>\n            <\/jats:inline-formula>, focusing on the versatility, ease of use, and competitive performance of the tool. <jats:inline-formula>\n              <jats:alternatives>\n                <jats:tex-math>$$_\\text {CAV25}$$<\/jats:tex-math>\n                <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:msub>\n                    <mml:mrow\/>\n                    <mml:mrow>\n                      <mml:mi>CAV<\/mml:mi>\n                      <mml:mn>25<\/mml:mn>\n                    <\/mml:mrow>\n                  <\/mml:msub>\n                <\/mml:math>\n              <\/jats:alternatives>\n            <\/jats:inline-formula> is available at: <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/dynaroars\/neuralsat\" ext-link-type=\"uri\">https:\/\/github.com\/dynaroars\/neuralsat<\/jats:ext-link>.<\/jats:p>","DOI":"10.1007\/978-3-031-98679-6_19","type":"book-chapter","created":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T09:21:17Z","timestamp":1753089677000},"page":"409-423","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["NeuralSAT: A High-Performance Verification Tool for\u00a0Deep Neural Networks"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3341-9794","authenticated-orcid":false,"given":"Hai","family":"Duong","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4255-4592","authenticated-orcid":false,"given":"ThanhVu","family":"Nguyen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1937-1544","authenticated-orcid":false,"given":"Matthew B.","family":"Dwyer","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,22]]},"reference":[{"key":"19_CR1","doi-asserted-by":"publisher","unstructured":"Althoff, M.: An introduction to Cora 2015. 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