Agents-K1: Towards Agent-native Knowledge Orchestration

• URL: http://arxiv.org/abs/2606.13669v1
• Date: Thu, 11 Jun 2026 17:58:35 GMT
• Title: Agents-K1: Towards Agent-native Knowledge Orchestration
• Abstract summary: textbfAgents-K1 is an end-to-end knowledge orchestration pipeline.<n>It converts raw documents into agent-native scientific knowledge graphs.<n>We process 2.46 million scientific papers across six subjects to produce textbfScholar-KG, of which we release a one-million-paper subset.
• Score: 59.22667222947257
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Current LLM-based research agents have advanced through agent orchestration, yet largely overlook scientific knowledge orchestration. Existing works often reduce papers to abstracts, surface mentions, and flat \texttt{cites} edges, omitting key entities, claims, evidence, mechanisms, and method lineages essential for scientific reasoning. To this end, we introduce \textbf{Agents-K1}, an end-to-end knowledge orchestration pipeline that converts raw documents into agent-native scientific knowledge graphs. Agents-K1 integrates three components under a unifying theoretical foundation: a multimodal parser whose five-module schema captures entities, multimodal evidence, citations, and typed inter-entity relations across the full paper rather than abstracts alone; a 4B information-extraction backbone trained with GRPO under a rule-based reward; and a graphanything CLI, a tri-source agent interface that unifies web search, multimodal graph retrieval, and cross-document traversal. On top of this, we process 2.46 million scientific papers across six subjects to produce \textbf{Scholar-KG}, of which we release a one-million-paper subset, and the full Scholar-KG is accessible via the SCP link below. The same pipeline can be extended to general-domain corpora and to schema-conformant data synthesis. Extensive experiments demonstrate that Agents-K1 achieves superior performance in scientific information extraction, knowledge graph construction, and multi-hop scientific reasoning.

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