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Axion 1.0: Open Agent Foundation Models, Simplified — arXiv:2611.03233

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.03233
License (as archived): CC0-1.0
Archived: 2026-11-03T10:54:32.201Z
SHA-256 of the archived text: ce7d9c96133693e0255b0641813ba00cf4f183a2a288c376e13820b28d184d57
Stable URL of this page: https://metraipolis.com/documento/dc_8a47ccfbf618

How to cite

Axion 1.0: Open Agent Foundation Models, Simplified — arXiv:2611.03233 — arXiv (en), https://arxiv.org/abs/2611.03233 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_8a47ccfbf618 (Metraipolis archive dc_8a47ccfbf618, sha256 ce7d9c96133693e0255b0641813ba00cf4f183a2a288c376e13820b28d184d57)

BibTeX

@misc{dc8a47ccfbf618,
  title = {Axion 1.0: Open Agent Foundation Models, Simplified — arXiv:2611.03233},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.03233},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_8a47ccfbf618; sha256 ce7d9c96133693e0255b0641813ba00cf4f183a2a288c376e13820b28d184d57},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.03233. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

We introduce Axion 1.0, a fully open agent foundation model that combines strong and broad agentic capabilities with a remarkably simple training recipe. Axion 1.0 is trained in only three stages: two lightweight supervised fine-tuning stages followed by reinforcement learning, without dedicated mid-training, direct preference optimization (DPO), or on-policy distillation (OPD). The first SFT stage develops strong self-contained reasoning through model-aware data construction, where we synthesize challenging problems and adversarially strengthen them based on the base model's own successful solution strategies. The second stage extends these capabilities to tool-dependent reasoning through a scalable pipeline for constructing diverse and automatically verifiable tasks grounded in real-world data sources and deterministic computation. Finally, reinforcement learning further strengthens long-horizon reasoning and interaction with external tools and environments. Despite this compact training recipe, Axion 1.0 achieves strong performance across a broad suite of agentic benchmarks and is competitive with leading commercial models on several of them. Equally importantly, Axion 1.0 is open beyond model weights: we release the complete recipe, including data construction, generation, filtering, verification, prompts, and training code, enabling the entire development process to be reproduced and extended. Axion 1.0 demonstrates that strong agent foundation models can be both open and simple, offering a practical and reproducible path toward advancing open agentic intelligence.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.AI, nuovi lavori del giorno).
Categorie arXiv: Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2611.03233 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-03T10:49:38.417Z dalla pagina https://arxiv.org/list/cs.AI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).