Introduces and evaluates triplet loss embedding techniques with repeated-term anchors, difficulty-balanced examples, and hard-example emphasis to improve neural ranking for Horn logic reasoning.
Artificial intelligence , volume=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
High Quality Embeddings for Horn Logic Reasoning
Introduces and evaluates triplet loss embedding techniques with repeated-term anchors, difficulty-balanced examples, and hard-example emphasis to improve neural ranking for Horn logic reasoning.