The work introduces a should-change/should-not-change evaluation suite for legal LLMs and the LexGuard adversarial framework that uses SMT solvers to enforce legal consistency.
Agents on the bench: Large language model based multi agent framework for trustworthy digital justice.arXiv preprint arXiv:2412.18697, 2024
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.AI 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Multi-agent deliberation frameworks for legal reasoning with LLMs match baseline performance but yield distinct answers that cover cases single models miss.
citing papers explorer
-
Which Changes Matter? Towards Trustworthy Legal AI via Relevance-Sensitive Evaluation and Solver-Grounded Reasoning
The work introduces a should-change/should-not-change evaluation suite for legal LLMs and the LexGuard adversarial framework that uses SMT solvers to enforce legal consistency.
-
Investigating Multi-Agent Deliberation in Law
Multi-agent deliberation frameworks for legal reasoning with LLMs match baseline performance but yield distinct answers that cover cases single models miss.