Agents-K1: Towards Agent-native Knowledge Orchestration

Published
Source
arXiv
Paper number
420
Field
AI / General
arXiv ID
2606.13669

Key points

  • The five-module schema structures full-text papers into metadata, explicit mention, implicit abstraction, citation intent, and inter-entity relation.
  • A 4B model trained with GRPO and a rule-based reward outperforms an 8B open-source model on 10 benchmarks and matches a 32B model on NER.
  • After processing 2.46 million papers, it builds Scholar-KG and releases 1 million papers across six fields: CS, chemistry, biology, earth science, physics, and materials.
  • GraphAnything CLI provides a unified interface that combines web search, multimodal graph retrieval, and cross-document traversal.
  • On FrontierScience-Research, it improves Gemini-3 from 7.9 percent to 24.6 percent and GPT-5.2 from 25.2 percent to 39.4 percent.
  • It reaches SOTA over nine graph-RAG baselines on HotpotQA, 2WikiMultiHopQA, and MuSiQue.

Paper links

External research summaries. These are not HDATF publications or measured product results.

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