CogniConsole: Externalizing Inference-Time Control as a Formal Abstraction for Reliable LLM Interactions
We challenge this by demonstrating that reliability is significantly influenced by \emph{inference-time control} -- the computational layer governing task framing and context selection. We introduce \emph{CogniConsole}, an architectural instantiation that externalizes this control into a structured interface combining programmatic coordination with bounded prompt-based reasoning. Through \emph{controllability-oriented probes} ($N=489$) in a multi-step interactive environment, we show that increasing structural scaffolding -- from unstructured to fully scaffolded -- \textbf{systematically reduces output variance and failure rates under a fixed model architecture}.
- ▪We challenge this by demonstrating that reliability is significantly influenced by \emph{inference-time control} -- the computational layer governing task framing and context selection.
- ▪We introduce \emph{CogniConsole}, an architectural instantiation that externalizes this control into a structured interface combining programmatic coordination with bounded prompt-based reasoning.
- ▪Through \emph{controllability-oriented probes} ($N=489$) in a multi-step interactive environment, we show that increasing structural scaffolding -- from unstructured to fully scaffolded -- \textbf{systematically reduces output variance and
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| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2607.08774 |
| Publication time | Mon, 13 Jul 2026 00:00:00 -0400 |
| Retrieval time | 2026-07-13T04:20:37.625Z |
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Computer Science > Artificial Intelligence arXiv:2607.08774 (cs) [Submitted on 21 Apr 2026] Title:CogniConsole: Externalizing Inference-Time Control as a Formal Abstraction for Reliable LLM Interactions Authors:Vanessa Figueiredo, Wilter Franceschi View a PDF of the paper titled CogniConsole: Externalizing Inference-Time Control as a Formal Abstraction for Reliable LLM Interactions, by Vanessa Figueiredo and Wilter Franceschi View PDF HTML (experimental) Abstract:Reliability in large language model (LLM) systems is typically framed as a function of model capability. We challenge this by demonstrating that reliability is significantly influenced by \emph{inference-time control} -- the computational layer governing task framing and context selection.
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