The paper proves that the reversible elementary second order cellular automaton rule 115 is periodic when started on finite initial configurations.

The paper introduces 'layered mutability,' a framework for analyzing how persistent self-modifying AI agents drift away from intended behavior due to the accumulation of locally reasonable, uncoordina…

The paper introduces a computational framework using Hodge zero-modes to track the geometry of topological features in parameter-dependent data, providing metrics like curvature and holonomy to quanti…

The paper validates a specialized mathematical metric (the Burau-Lyapunov exponent) designed for detecting privilege escalation in cloud IAM graphs by applying it to an unrelated physical system: sola…

The paper proves that standard runtime enforcement mechanisms cannot detect systematic behavioral drift in autonomous agents, proposing a new Invariant Measurement Layer (IML) that restores observabil…

The paper reformulates nonreversible perturbations of Fokker--Planck dynamics as gauge fields, providing a unified operator viewpoint to analyze relaxation processes and develop methods for learning o…

The paper models latent worker preferences in gig labor markets using the Preisach hysteresis model, demonstrating that predicting acceptance rates can simultaneously reduce labor costs and increase s…

This paper addresses the security vulnerabilities in drone swarm control algorithms by proposing two fuzzing tools, SwarmFuzzGraph and SwarmFuzzBinary, to discover Swarm Propagation Vulnerabilities (S…

The paper demonstrates that the phenomenon of 'subliminal learning,' where behavioral traits are transmitted between language models, is not a fundamental learning mechanism but rather a fragile artif…

The paper provides a unified algebraic framework to determine the formal language expressivity of recurrent neural language models, resolving conflicts in existing literature by linking expressivity t…

The paper proposes Periodic RoPE (P-RoPE) combined with a dual-layer attention mechanism to overcome the positional encoding limitations of LLMs, enabling theoretically infinite context understanding.

This paper analyzes the computational complexity of evaluating recurrent functions, showing that the complexity depends heavily on how the input offsets are encoded and the structure of the recurrence…

This paper establishes the identifiability of latent regimes and regime-dependent causal structures in complex non-stationary time series modeled by Markov Switching Models, even with instantaneous ef…

The paper introduces Agent Control Protocol (ACP), a stateful temporal admission control mechanism that enforces behavioral properties over execution traces to prevent harmful patterns from individual…

The Parameterized Diffusion Policy (PDP) framework transforms diffusion models from general stochastic generators into precise, steerable tools for learning and adapting complex robotic behaviors by e…

The paper proposes an engineering framework, inspired by metamaterials physics, to quantify institutional coordination and predict civilizational stability in the age of AI.

The paper proposes a novel set of combined cellular automaton (CA)-based pseudo-random number generators (PRNGs) that overcome the weak equidistribution issues of existing CA-based PRNGs, achieving ma…

SeqWM introduces a sequential behavioral watermarking framework that embeds ownership signals into history-conditioned transition patterns of LLM agent actions, providing robust and position-agnostic…

The paper establishes a unified framework for timed opacity by introducing a universal observation model and defining evolution-based timed opacity, proving its relationship to existing opacity defini…

The paper introduces FP-Agent, a classifier that demonstrates that while browser fingerprints are poor discriminators for AI browsing agents, behavioral fingerprints (like typing and scrolling pattern…