{"slug": "cogniconsole-externalizing-inference-time-control-as-a-formal-abstraction-for", "title": "CogniConsole: Externalizing Inference-Time Control as a Formal Abstraction for Reliable LLM Interactions", "summary": "Researchers introduced CogniConsole, an architecture that externalizes inference-time control for LLMs through a structured interface combining programmatic coordination with bounded prompt-based reasoning. In a study with 489 controllability-oriented probes, they found that increasing structural scaffolding systematically reduces output variance and failure rates, suggesting many LLM failures stem from under-specified control rather than insufficient capability.", "body_md": "arXiv:2607.08774v1 Announce Type: new\nAbstract: 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. 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}. Our results indicate that many observed failure modes, such as context drift and inconsistent constraint adherence, arise from under-specified control rather than insufficient capability. This work provides an empirical basis for treating inference-time control as a first-class abstraction, opening new directions for designing and evaluating LLM systems beyond scaling alone.", "url": "https://wpnews.pro/news/cogniconsole-externalizing-inference-time-control-as-a-formal-abstraction-for", "canonical_source": "https://arxiv.org/abs/2607.08774", "published_at": "2026-07-13 04:00:00+00:00", "updated_at": "2026-07-13 04:07:47.909801+00:00", "lang": "en", "topics": ["large-language-models", "ai-research", "ai-safety"], "entities": ["CogniConsole"], "alternates": {"html": "https://wpnews.pro/news/cogniconsole-externalizing-inference-time-control-as-a-formal-abstraction-for", "markdown": "https://wpnews.pro/news/cogniconsole-externalizing-inference-time-control-as-a-formal-abstraction-for.md", "text": "https://wpnews.pro/news/cogniconsole-externalizing-inference-time-control-as-a-formal-abstraction-for.txt", "jsonld": "https://wpnews.pro/news/cogniconsole-externalizing-inference-time-control-as-a-formal-abstraction-for.jsonld"}}