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On Measuring Semantic Preservation in Legal Ontology Learning
Researchers introduce a new evaluation methodology to measure semantic loss during ontology learning—specifically how meaning degrades when converting unstructured legal text into structured representations—and demonstrate it on merger agreement analysis across six LLMs and three ontology methods.
Aug 14, 2026
Automated Reasoning policy refinement in Amazon Bedrock
Amazon Bedrock introduces automated policy refinement for Automated Reasoning Guardrails, enabling AI developers to auto-diagnose and propose formal-logic fixes for failing safety policies—requiring human approval before deployment—to reduce manual tuning friction in enterprise AI governance.
Aug 3, 2026
KARMA: Knowledge graph-based Automated Reasoning Materialization and Alignment
KARMA is a new contrastive synthesis method that uses knowledge graphs to generate slot-aligned candidates and applies slot-level supervision to improve preference learning in LLMs.
Jul 8, 2026