{"id":661,"date":"2025-03-08T12:33:10","date_gmt":"2025-03-08T11:33:10","guid":{"rendered":"https:\/\/www.evostar.org\/2026\/?page_id=661"},"modified":"2026-02-18T22:53:44","modified_gmt":"2026-02-18T21:53:44","slug":"eurogp-accepted-papers","status":"publish","type":"page","link":"https:\/\/www.evostar.org\/2026\/eurogp-accepted-papers\/","title":{"rendered":"EuroGP Accepted Papers"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Long talks<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>On the Effects of Down-Sampling for Tournament and Lexicase Selection in Program Synthesis<br><em>Martin Briesch<\/em><\/li>\n\n\n\n<li>Comparison of parent and environmental selection schemes in genetic programming for symbolic regression<br><em>Vladimir Stanovov<\/em><\/li>\n\n\n\n<li>A Comparative Study on Robustness in Evolved Image Classifiers<br><em>Camilo De La Torre, St\u00e9phane Treillard, Camille Franchet, Herve Luga, Dennis Wilson and Sylvain Cussat-Blanc<\/em><\/li>\n\n\n\n<li>Syntactic Flexibility Enables Compact Solutions in Transformer Semantic GP<br><em>Philipp Anthes<\/em><\/li>\n\n\n\n<li>Node Preservation and its Effect on Crossover in Cartesian Genetic Programming<br><em>Mark Kocherovsky, Illya Bakurov and Wolfgang Banzhaf<\/em><\/li>\n\n\n\n<li>New Perspectives on Cartesian Genetic Programming: A Survey<br><em>Mark Kocherovsky, Henning Cui, Illya Bakurov, Michael Heider, Roman Kalkreuth and Wolfgang Banzhaf<\/em><\/li>\n\n\n\n<li>Semantic Search Trajectory Networks for Understanding Genetic Programming<br><em>Josip Hrvati\u0107, Magda Smoli\u0107-Ro\u010dak, Marko \u0110urasevi\u0107 and Gabriela Ochoa<\/em><\/li>\n\n\n\n<li>A Hybrid LLM-Coevolution Framework to Generate Abusive Tax Strategies<br><em>Joy Bhattacharaya, Erik Hemberg and Unamay O&#8217;Reilly<\/em><\/li>\n\n\n\n<li>Sinking the Bloat in Genetic Programming Using Equality Saturation<br><em>Lucas Miranda, Emilio Francesquini, Fabricio de Franca and Matheus Fernandes<\/em><\/li>\n\n\n\n<li>Revisiting SLIM: Improved Learning Dynamics and Model Compactness in Symbolic Regression<br><em>Gorka Silva, Lachlan Stewart, Illya Bakurov, Mauro Castelli, Davide Farinati, Jose Manuel Mu\u00f1oz Contreras, Leonardo Trujillo and Leonardo Vanneschi<\/em><\/li>\n\n\n\n<li>Dynamic Vector and Matrix Memory for Tangled Program Graphs<br><em>Ali Naqvi and Stephen Kelly<\/em><\/li>\n\n\n\n<li>Extending Model Selection Criteria with Extrapolation and Sensitivity Penalties for Symbolic Regression<br><em>Fitria Wulandari Ramlan, Colm O&#8217;Riordan and James McDermott<\/em><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Short talks<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Optimal Mixing in Graph-Based GP for Control: Genotypical Dependencies Are Hardly Captured<br><em>Giorgia Nadizar, Gloria Pietropolli and Eric Medvet<\/em><\/li>\n\n\n\n<li>Multi-tree Genetic Programming with Semantic Complementarity for Feature Construction in Symbolic Regression<br><em>Jiayu Zhang, Qi Chen, Bing Xue and Mengjie Zhang<\/em><\/li>\n\n\n\n<li>NEVO-GSPT: Population-Based Neural Network Evolution Using Inflate and Deflate Operators<br><em>Davide Farinati, Frederico J.J.B. Santos, Leonardo Vanneschi and Mauro Castelli<\/em><\/li>\n\n\n\n<li>Multi-Action Tangled Program Graphs for Multi-Task Reinforcement Learning with Continuous Control<br><em>Quentin Vacher, Nicolas Beuve, Micka\u00ebl Dardaillon and Karol Desnos<\/em><\/li>\n\n\n\n<li>Reducing Computational Overhead in Biomedical Image Segmentation via Active Learning and PCA-Based Diversity Filtering in CGP<br><em>Yuri Lavinas, Wolfgang Banzhaf, Sylvain Cussat-Blanc and Nathaniel Haut<\/em><\/li>\n\n\n\n<li>Exploring CGP Fitness Landscapes with MCTS<br><em>Christina Berghegger, Camilo De La Torre, Sylvain Cussat-Blanc, Yuri Lavinas and David Simoncini<\/em><\/li>\n\n\n\n<li>Extended Semantics Operator for Genetic Programming: A Semantic-Density Approach to Improve Model Robustness<br><em>Sofia Pereira and Leonardo Vanneschi<\/em><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Long talks Short talks<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-661","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.evostar.org\/2026\/wp-json\/wp\/v2\/pages\/661","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.evostar.org\/2026\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.evostar.org\/2026\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.evostar.org\/2026\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.evostar.org\/2026\/wp-json\/wp\/v2\/comments?post=661"}],"version-history":[{"count":12,"href":"https:\/\/www.evostar.org\/2026\/wp-json\/wp\/v2\/pages\/661\/revisions"}],"predecessor-version":[{"id":1291,"href":"https:\/\/www.evostar.org\/2026\/wp-json\/wp\/v2\/pages\/661\/revisions\/1291"}],"wp:attachment":[{"href":"https:\/\/www.evostar.org\/2026\/wp-json\/wp\/v2\/media?parent=661"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}