LegalSearch-R1 trains a 7B agent via RL on multi-period legal data with hybrid RAG/web search to improve temporal consistency, reporting 12.9-29.8% gains over SOTA and 57.7-80.3% on consistency metrics across 13 tasks.
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DocArena automates creation of multimodal document QA training data via MLLM-based structuring and cross-page reasoning pairs, yielding agents with top retrieval and QA performance in unified tests.
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Can LLMs Time Travel? Enhancing Temporal Consistency in Legal Agentic Search through Reinforcement Learning
LegalSearch-R1 trains a 7B agent via RL on multi-period legal data with hybrid RAG/web search to improve temporal consistency, reporting 12.9-29.8% gains over SOTA and 57.7-80.3% on consistency metrics across 13 tasks.
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DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents
DocArena automates creation of multimodal document QA training data via MLLM-based structuring and cross-page reasoning pairs, yielding agents with top retrieval and QA performance in unified tests.