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Related Articles from SNS
From Storage to Steering: Memory Control Flow Attacks on LLM Agents
Announce Type: replace Abstract: Modern agentic systems allow Large Language Model (LLM) agents to tackle complex tasks through extensive tool usage, forming structured control flows of tool selection and execution. Existing security analyses often treat these control flows as ephemeral, one-off sessions, overlooking the persistent influence of memory. This paper identifies a new threat from Memory Control Flow Attacks (MCFA) that memory can dominate the control flow, forcing unintended tool...
Constrained Control of PDE Traffic Flow via Spatial Control Barrier Functions
Announce Type: replace Abstract: In this paper, a constrained control approach to variable speed limit (VSL) control for macroscopic partial differential equations (PDE) traffic models is developed. Control Lyapunov function (CLF) theory for ordinary differential equations (ODE) is extended to account for spatially and temporally varying states and control inputs. The stabilizing CLF is then unified with safety constraints through the introduction of spatially varying control barrier...
Data Flow Control: Data Safety Policies for AI Agents
Announce Type: new Abstract: Agents increasingly generate SQL, orchestrate pipelines, and automate data analysis on behalf of users. While recent work improves query correctness, correctness is not safety. A query may be semantically valid yet violate regulatory, privacy, or business constraints that govern how data may be combined and released.
From Statute to Control Flow: Span-Grounded Deontic Trees for Defeasible Scope Parsing
Announce Type: new Abstract: Rule-following agents tasked with executing policies and regulations often fail via Silent Scope Omission (SSO): a model applies a general rule but silently drops nested exceptions or counter-exceptions, producing outputs that appear compliant yet break on important edge cases. Although such failures are often framed as an agentic-systems problem, the underlying bottleneck is statutory and policy understanding, a capability typically studied in legal NLP....
Non-Vacuous Certification of Transport MCMC via Oscillation-Controlled Normalizing Flows
arXiv:2606.01078v1 Announce Type: new Abstract: Transport MCMC trains a normalizing flow to precondition Metropolis--Hastings proposals, achieving high empirical efficiency on challenging posteriors; yet no prior work produces a numerically non-vacuous, rigorous spectral-gap bound for such samplers. We establish the first such bounds. For independence MH on the banana family we certify (\gamma^\ast = 0.828) at (D = 2) (covering in the original space) and (\gamma^\ast \ge 7.6\times 10^{-4})...
Optimal Finite-Horizon LQR Control for Traffic Flow via Variable Speed Limits
Announce Type: replace-cross Abstract: This article presents a finite-horizon linear quadratic regulator for the control of the first-order Lighthill-Whitham-Richards traffic model with a triangular fundamental diagram. The in-domain control action is realized through variable speed limits implemented as a source term in the governing hyperbolic partial differential equation. Unlike prior studies on infinite-horizon formulations, this article develops a finite-horizon LQR framework, deriving...
Optimal Finite-Horizon LQR Control for Traffic Flow via Variable Speed Limits
arXiv:2606.03632v1 Announce Type: cross Abstract: This article presents a finite-horizon linear quadratic regulator for the control of the first-order Lighthill-Whitham-Richards traffic model with a triangular fundamental diagram. The in-domain control action is realized through variable speed limits implemented as a source term in the governing hyperbolic partial differential equation.
Toward automatic generation of control structures for process flow diagrams with large language models
arXiv:2211.05583v2 Announce Type: replace Abstract: Developing Piping and Instrumentation Diagrams (P&IDs) is a crucial step during process development. We propose a data-driven method for the prediction of control structures. Our methodology is inspired by end-to-end transformer-based human language translation models.
Solving Inverse Problems with Flow-based Models via Model Predictive Control
arXiv:2601.23231v2 Announce Type: replace-cross Abstract: Flow-based generative models provide strong unconditional priors for inverse problems, but guiding their dynamics for conditional generation remains challenging. Recent work casts training-free conditional generation in flow models as an optimal control problem; however, solving the resulting trajectory optimisation is computationally and memory intensive, requiring differentiation through the flow dynamics or adjoint solves. We...
Role of boundary conditions on dam-break flow across an obstacle and controlling damage of structures
arXiv:2606.05580v1 Announce Type: new Abstract: We studied dam-break flow in the smoothed particle hydrodynamics framework using periodic boundary condition (PBC) instead of usually employed rigid wall boundary condition (WBC) and assessed the effects of impact of the flow on the downstream structure due to the presence of an obstacle in front of it. The results show that higher dam heights lead to larger pressure on the wall. The WBC yields higher peak pressures compared PBC.