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Bridging Machine Learning and Logical Reasoning by Abductive Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| abductive learning (CNN + logical abduction) vs end-to-end neural nets | handwritten equation decipherment · DBA and RBA | accuracy | Helped |
| train ABL on only length 5-8 equations (ABL-short) instead of all (ablation) | ABL · DBA and RBA | accuracy | No clear effect |
| abductive learning with logic background knowledge vs CNN | extended n-queens · MNIST chessboards | accuracy: 0.736 ± 0.016 -> 0.981 ± 0.006 | Helped |
| abductive learning vs Bi-LSTM | extended n-queens · MNIST chessboards | accuracy: 0.513 ± 0.013 -> 0.976 ± 0.008 | Helped |
| swap abduction engine (ALP, CHR, CLP(FD)) (ablation) | ABL · extended n-queens | accuracy: 0.976 / 0.979 / 0.981 | No clear effect |
| transfer CNN learned on DBA (perception transfer) (ablation) | ABL · XOR equations | convergence speed | Helped |
| transfer knowledge model from RBA to DBA (ablation) | ABL · DBA | convergence speed | Helped |
| ABL vs human volunteers | equation classification · DBA and RBA | accuracy | Helped |
Closest papers by meaning
- Ambiguity-Aware Abductive Learning (ICML 2024 · similarity 0.87)
- Curriculum Abductive Learning (NeurIPS 2025 · similarity 0.86)
- Efficient Rectification of Neuro-Symbolic Reasoning Inconsistencies by Abductive Reflection (AAAI 2025 · similarity 0.85)
- Analysis for Abductive Learning and Neural-Symbolic Reasoning Shortcuts (ICML 2024 · similarity 0.85)
- Safe Abductive Learning in the Presence of Inaccurate Rules (AAAI 2024 · similarity 0.85)
- RMath: A Logic Reasoning-Focused Datasets Toward Mathematical Multistep Reasoning Tasks (AAAI 2025 · similarity 0.84)
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