Research map / Label-efficient and robust learning / Recognition and long-tail
Practical TBox Abduction Based on Justification Patterns
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| restrict explanations to cardinality 1 rather than 2 | JP-based explanation computation · LUBM TBox, 50 observations | computation time (s): 178.8 -> 3.9 | Helped |
| restrict explanations to cardinality 1 on wine | JP-based explanation computation · wine TBox, 50 observations | number of JP-based explanations: 10948 (k=2) vs 0 (k=1) | Hurt |
| compute justification patterns alternately with justifications rather than all justifications first | JP computation · ten coherent TBoxes | computation time | Helped |
Closest papers by meaning
- An Improved Algorithm for Learning to Perform Exception-Tolerant Abduction (AAAI 2017 · similarity 0.86)
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- Learning Abduction Using Partial Observability (AAAI 2018 · similarity 0.85)
- Learning Abductive Reasoning Using Random Examples (AAAI 2016 · similarity 0.85)
- From Probability to Counterfactuals: the Increasing Complexity of Satisfiability in Pearl's Causal Hierarchy (ICLR 2025 · similarity 0.83)
- Axiomatic Aggregations of Abductive Explanations (AAAI 2024 · similarity 0.81)
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