arXiv:2605.05287v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) and agentic AI systems are increasingly prevalent in enterprise AI deployments. However, real enterprise environments introduce challenges largely absent from academic treatments and consumer-facing APIs: multiple tenants with heterogeneous data, strict access-control requirements, regulatory compliance, and cost pressures that demand shared infrastructure. A fundamental problem underlies existing […]
The Geopolitics of AI Safety: A Causal Analysis of Regional LLM Bias
arXiv:2605.05427v1 Announce Type: new Abstract: As Large Language Models (LLMs) are integrated into global software systems, ensuring equitable safety guardrails is a critical requirement. Current fairness evaluations predominantly measure bias observationally, a methodology confounded by the inherent toxicity of topics naturally paired with specific demographics in testing datasets. This study introduces a Probabilistic Graphical Model […]
COPYCOP: Ownership Verification for Graph Neural Networks
arXiv:2605.05360v1 Announce Type: cross Abstract: Given two GNNs that output node embeddings, how can we determine if they were trained independently? An adversary could have trained one GNN specifically to mimic the other GNN’s embeddings. To obscure this relationship between the GNNs, the adversarial GNN might then transform its output embeddings. The two GNNs could […]
Tracking Capabilities for Safer Agents
arXiv:2603.00991v2 Announce Type: replace Abstract: AI agents that interact with the real world through tool calls pose fundamental safety challenges: agents might leak private information, cause unintended side effects, or be manipulated through prompt injection. To address these challenges, we propose to put the agent in a programming-language-based “safety harness”: instead of calling tools directly, […]
Creative Robot Tool Use by Counterfactual Reasoning
arXiv:2605.05411v1 Announce Type: cross Abstract: We propose a causal reasoning framework for creative robot tool use where a suitable tool for a task is correctly identified for use beyond its primary objectives. The proposed framework first discovers the causal relationships between the tool and the task by conducting simulated experiments in a dynamics model. We […]
Authorization Propagation in Multi-Agent AI Systems: Identity Governance as Infrastructure
arXiv:2605.05440v1 Announce Type: new Abstract: The security discussion around agentic AI focuses heavily on prompt injection. This paper argues that multi-agent systems also create a distinct authorization problem: maintaining authorization invariants as non-human principals retrieve data, delegate tasks, and synthesize results across changing boundaries. We call this problem authorization propagation. It is not reducible to […]
ReaComp: Compiling LLM Reasoning into Symbolic Solvers for Efficient Program Synthesis
arXiv:2605.05485v1 Announce Type: cross Abstract: LLMs can solve program synthesis tasks but remain inefficient and unreliable on hard instances requiring large combinatorial search. Given a small set of reasoning traces, we use coding agents to compile them into reusable symbolic program synthesizers over constrained DSLs. The resulting solvers require no LLM calls at test time […]
Leveraging Image Generators to Address Training Data Scarcity: The Gen4Regen Dataset for Forest Regeneration Mapping
arXiv:2605.05627v1 Announce Type: cross Abstract: Sustainable forest management relies on precise species composition mapping, yet traditional ground surveys are labour-intensive and geographically constrained. While Uncrewed Aerial Vehicles (UAVs) offer scalable data collection, the transition to deep learning-based interpretation is bottlenecked by the severe scarcity of expert-annotated imagery, particularly in complex, visually heterogeneous regeneration zones. This […]
Agentic Discovery of Exchange-Correlation Density Functionals
arXiv:2605.05460v1 Announce Type: new Abstract: The development of accurate exchange-correlation (XC) functionals remains a longstanding challenge in density functional theory (DFT). The vast majority of XC functionals have been hand designed by human researchers combining physical insight, exact constraints, and empirical fitting. Recent advances in large language models enable a systematic, automated alternative to this […]
CFE-PPAR: Compression-friendly encryption for privacy-preserving action recognition leveraging video transformers
arXiv:2605.05692v1 Announce Type: cross Abstract: Privacy-preserving action recognition (PPAR) enables machines to understand human activities in videos without revealing sensitive visual content. Among the various strategies for PPAR, encryption-based methods achieve strong privacy protection while maintaining high recognition performance. However, these methods lead to a catastrophic decrease in recognition performance and visual quality when the […]
WARP: A Benchmark for Primal-Dual Warm-Starting of Interior-Point Solvers
arXiv:2605.05728v1 Announce Type: cross Abstract: Solving AC Optimal Power Flow (AC-OPF) is of central importance in electricity market operations, where interior-point methods (IPMs) such as IPOPT are the standard solvers. A growing body of work uses machine learning to predict primal warm-start iterates, reporting iteration reductions of 30-46%. We show that these reported gains rest […]
The Origin of Life in the Light of Evolution
arXiv:2605.05464v1 Announce Type: new Abstract: The origin of life is often framed primarily as a chemical problem, yet life’s defining feature is evolution. Advances in geochemistry, prebiotic chemistry, and molecular biology have produced diverse scenarios for the emergence of genomes, metabolism, and cellular compartments on the early Earth, but most of these models lack a […]