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AgentFounder: Scaling Agents via Continual Pre-training ā¢ First to propose Agentic CPT ā builds agentic foundation models before fine-tuning ā¢ Solves post-training bottlenecks (capabilities + alignment conflict) ā¢ Data synthesis: First-order (planning/actions) + Higher-order (multi-step decision) ā¢ Two-stage training (32K ā 128K context) ā¢ SOTA: 39.9% BrowseComp-en, 72.8% GAIA abs: https://t.co/LTCuW2LCo4 (5/N)
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