Metraipolis › archive › dc_787e07301ffd

Dual Exam: Controlled Evaluation of Multimodal Agents and World Models — arXiv:2610.31066

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.31066
License (as archived): CC0-1.0
Archived: 2026-10-25T08:32:51.304Z
SHA-256 of the archived text: a30d0cbe30548bb09fb7c9fb1494bf18186dc13f6a1d2fb810f2e33b36e29faf
Stable URL of this page: https://metraipolis.com/documento/dc_787e07301ffd

How to cite

Dual Exam: Controlled Evaluation of Multimodal Agents and World Models — arXiv:2610.31066 — arXiv (en), https://arxiv.org/abs/2610.31066 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_787e07301ffd (Metraipolis archive dc_787e07301ffd, sha256 a30d0cbe30548bb09fb7c9fb1494bf18186dc13f6a1d2fb810f2e33b36e29faf)

BibTeX

@misc{dc787e07301ffd,
  title = {Dual Exam: Controlled Evaluation of Multimodal Agents and World Models — arXiv:2610.31066},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.31066},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_787e07301ffd; sha256 a30d0cbe30548bb09fb7c9fb1494bf18186dc13f6a1d2fb810f2e33b36e29faf},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.31066. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

World Models (WMs) can support Multimodal Agents (MAs) through simulated experience, while Agent trajectories can inform World Model refinement. Evaluating this interaction requires separate evidence about action selection and state evolution. We introduce Dual Exam, which tests Agents under fixed environment response mechanisms and World Models under fixed action interventions across physical, digital, social, and scientific domains. The Agent track compares 10 configurations on 1,088 items in 15 reporting categories. The World Model track contains 400 cases across eight scenarios; 15 configurations have full coverage and one covers six scenarios. GPT 6 Astra leads the case-weighted Agent Index at 31.3, and GPT-Image-2 leads the full-coverage WM Overall at 21.7. These scores use different tasks and metrics and are not directly comparable. A 150-case pilot of one coupled pairing records zero task successes and motivates component-level diagnosis. Results reveal uneven task performance and failures to preserve task-relevant state. Their value for predicting coupled success or sustained reciprocal learning remains to be established.

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/2610.31066 — 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 2026-10-25T08:31:13.062Z dalla pagina https://arxiv.org/list/cs.AI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).