With a fixed agent harness and clingo in the loop, three of four frontier LLMs distill complete ASP theories scoring 93–100% on CLEVR, GQA, and CLEVRER from scratch in one hour.
d'Avila Garcez
4 Pith papers cite this work, alongside 30 external citations. Polarity classification is still indexing.
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representative citing papers
AttackPathGNN introduces a State Interference Graph and conjunction pooling inside a GNN to detect cross-function vulnerabilities in Solidity contracts, reporting 92.3% F1 on SmartBugs Wild.
LLM-scored offer predicates aggregated by a Logic Tensor Network classify procurement documents about as accurately as BERT or LLM baselines while exposing auditable predicate and rule truth values.
NeurASP extends answer set programming with neural network outputs as probability distributions over atomic facts, improving perception accuracy and enabling logic-guided training.
citing papers explorer
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AttackPathGNN: Cross-function vulnerability detection in smart contracts using state interference graphs and conjunction pooling
AttackPathGNN introduces a State Interference Graph and conjunction pooling inside a GNN to detect cross-function vulnerabilities in Solidity contracts, reporting 92.3% F1 on SmartBugs Wild.