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Partial Label Learning for Automated Theorem Proving

arXiv 2507.03314 ↗First posted 4 Jul 2025cs.LO cs.AIcited by 0

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Abstract (arXiv)

We formulate learning guided Automated Theorem Proving as Partial Label Learning, building the first bridge across these fields of research and providing a theoretical framework for dealing with alternative proofs during learning. We use the plCoP theorem prover to demonstrate that methods from the Partial Label Learning literature tend to increase the performance of learning assisted theorem provers.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 19 of its 36 references that are in the map. First posted on arXiv 4 Jul 2025.

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References · 19

  1. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166
  2. 2017Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithmcited by 734
  3. 2017Thinking Fast and Slow with Deep Learning and Tree Searchcited by 252
  4. 2020Provably Consistent Partial-Label Learningcited by 92
  5. 2016DeepMath - Deep Sequence Models for Premise Selectioncited by 81
  6. 2018Reinforcement Learning of Theorem Provingcited by 69
  7. 2021Leveraged Weighted Loss for Partial Label Learningcited by 66
  8. 2019Graph Representations for Higher-Order Logic and Theorem Provingcited by 55
  9. 2017Deep Network Guided Proof Searchcited by 47
  10. 2019Partial Label Learning with Self-Guided Retrainingcited by 47
  11. 2017Premise Selection for Theorem Proving by Deep Graph Embeddingcited by 44
  12. 2017From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihoodcited by 41
7 more
  1. 2017ENIGMA: Efficient Learning-based Inference Guiding Machinecited by 26
  2. 2019Property Invariant Embedding for Automated Reasoningcited by 22
  3. 2018ATPboost: Learning Premise Selection in Binary Setting with ATP Feedbackcited by 12
  4. 2019Towards Finding Longer Proofscited by 10
  5. 2021The Role of Entropy in Guiding a Connection Provercited by 8
  6. 2013MaLeS: A Framework for Automatic Tuning of Automated Theorem Proverscited by 3
  7. 2023Towards Unbiased Exploration in Partial Label Learningcited by 2

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