LawCompass: Navigating from Legal QA to Multi-Agent Deep Research with Grounded Evidence
Recent advances in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) have significantly democratized access to legal information. Nevertheless, most existing legal assistants remain confined to multi-turn conversational QA, failing to support complex legal tasks that require systematic evidence retrieval, multi-step reasoning, and report-level synthesis. In this paper, we present LawCompass, an evidence-grounded legal assistant that navigates the transition from standard Legal QA to multi-agent deep research. LawCompass provides three task-oriented functions: Legal QA, which delivers precise, evidence-backed answers to legal questions; Professional Retrieval, which ena...
| Authors | Xiaoxia Cheng, Linnan Wang, Jiahao Ma et al. |
|---|---|
| Primary category | cs.CL |
| Published | 1 October 2026 |
| Last updated at source | 1 October 2026 |
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