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Agentic Cognitive Depth: Operational Criteria for Evaluating LLM Agents — arXiv:2610.04168

Source: arXiv
Original: https://arxiv.org/abs/2610.04168
License (as archived): CC0-1.0
Archived: 2026-10-06T05:24:20.092Z
SHA-256 of the archived text: 1af83275197bfe5bf26bb018f7bafdd4e4a32f9513e798ae04b00791148a27f1
Stable URL of this page: https://metraipolis.com/documento/dc_ca41cdb9ef80

How to cite

Agentic Cognitive Depth: Operational Criteria for Evaluating LLM Agents — arXiv:2610.04168 — arXiv, https://arxiv.org/abs/2610.04168 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ca41cdb9ef80 (Metraipolis archive dc_ca41cdb9ef80, sha256 1af83275197bfe5bf26bb018f7bafdd4e4a32f9513e798ae04b00791148a27f1)

BibTeX

@misc{dcca41cdb9ef80,
  title = {Agentic Cognitive Depth: Operational Criteria for Evaluating LLM Agents — arXiv:2610.04168},
  howpublished = {arXiv},
  url = {https://arxiv.org/abs/2610.04168},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ca41cdb9ef80; sha256 1af83275197bfe5bf26bb018f7bafdd4e4a32f9513e798ae04b00791148a27f1},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv, https://arxiv.org/abs/2610.04168. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Agentic large language model (LLM) systems are commonly implemented as an LLM in a loop with Planning, Memory, Tools, and Control Flow. This application-focused view connects agentic LLM research with deployable systems and leaves open how such systems should be evaluated beyond end-to-end task success. Building on this view, we define agentic cognitive depth as a trajectory-level profile across five operational criteria. The profile contains context sensitivity ($C$), temporal continuity ($T$), multimodal coordination ($M$), adaptive interaction ($A$), and metacognitive monitoring ($Mc$). The first four criteria measure how well Control Flow, Memory, Tools, and Planning are used across a trajectory. The fifth measures whether the system monitors and regulates the full run. For each criterion, we give operational proxies and a perturbation procedure, then connect the profile to the agent's world model. We provide the structure needed to extend benchmarks such as GAIA, SWE-bench, WebArena, and TRIP-Bench with per-criterion diagnostics. Symbolic verifiers, structured memory, planner coupling, and tool constraints provide practical ways to build and test these capacities.

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/2610.04168 — 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 2026-10-06T05:24:05.433Z dalla pagina https://arxiv.org/list/cs.AI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).