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TOPIC · ENTITY #6803

cognitive science

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RESEARCH · 1 SOURCE · arXiv cs.AI

Before Agents Decide: Epistemic Action in LLM-Based Systems

New arXiv preprint (arXiv:2610.00511v1) brings the cognitive-science concept of epistemic actions to LLM-based agents, distinguishing three modes—acquiring missing evidence, transforming available evidence, and probing systems to elicit revealing responses—and introduces the term epistemic scaffolding for interfaces, tools, and environments that enable and make such actions auditable. The paper argues agent design should explicitly address how decision-ready evidence is produced before a decision step.

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RESEARCH · 1 SOURCE · arXiv cs.AI

Survey paper formalizes the Linear Representation Hypothesis (arXiv:2609.22695v1)

A new survey (arXiv:2609.22695v1) analyzes inconsistencies in how the "linear representation hypothesis" (LRH) has been used across AI, neuroscience, and cognitive science, arguing that prior work often lacks a falsifiable framing. The paper proposes a more rigorous formalization that makes dependencies on model, representation location, feature definition, and evaluation dataset explicit, and it identifies open problems for further research.

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