Symbolic Computation

Papers

• EM-NeSy: Expectation Maximization for Neurosymbolic Learning (2026)
  Annegret Seibt et al.
  4.39
• How Post-Training Shapes Biological Reasoning Models (2026)
  Lukas Fesser et al.
  3.51
• On the Generalization Bounds of Symbolic Regression with Genetic Programming (2026)
  Masahiro Nomura et al.
  3.39
• UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models (2026)
  Hyunju Kang et al.
  2.00
• SD-Search: On-Policy Hindsight Self-Distillation for Search-Augmented Reasoning (2026)
  Yufei Ma et al.
  2.00
• What Makes Effective Supervision in Latent Chain-of-Thought: An Information-Theoretic Analysis (2026)
  Xinghao Chen et al.
  2.00
• SCULPT: Constraint-guided Pruned MCTS That Carves Efficient Paths For Mathematical Reasoning (2026)
  Qitong Fang, Haotian Li, Xu Wang
  2.00
• Reason Only When Needed: Efficient Generative Reward Modeling Via Model-internal Uncertainty (2026)
  Chao Xue, Yao Wang, Mengqiao Liu, et al.
  2.00
• Hilbert-Geo: Solving Solid Geometric Problems by Neural-Symbolic Reasoning (2026)
  Ruoran Xu et al.
  1.94
• The Initial Exploration Problem in Knowledge Graph Exploration (2026)
  Claire McNamara et al.
  1.78
• Handling Infinite Domain Parameters in Planning Through Best-First Search with Delayed Partial Expansions (2025)
  \'Angel Aso-Mollar and Diego Aineto and Enrico Scala and Eva Onaindia
  1.50
• Learning To Ponder: Adaptive Reasoning In Latent Space (2025)
  Yixin He, Lumingyuan Tang
  1.33
• Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics (2025)
  Conor F. Hayes et al.
  1.28
• Fully Geometric Multi-Hop Reasoning on Knowledge Graphs with Transitive Relations (2025)
  Fernando Zhapa-Camacho et al.
  1.28
• KnowPath: Knowledge-enhanced Reasoning via LLM-generated Inference Paths over Knowledge Graphs (2025)
  Qi Zhao et al.
  1.11
• Chronosymbolic Learning: Efficient CHC Solving with Symbolic Reasoning and Inductive Learning (2023)
  Ziyan Luo and Xujie Si
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