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◬ AI & Machine Learning Apr 13, 2026
Hidden in Plain Sight: Visual-to-Symbolic Analytical Solution Inference from Field Visualizations

arXiv:2604.08863v1 Announce Type: new Abstract: Recovering analytical solutions of physical fields from visual observations is a fundamental yet underexplored capability for AI-assisted scientific rea…

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◬ AI & Machine Learning Apr 13, 2026
Artifacts as Memory Beyond the Agent Boundary

arXiv:2604.08756v1 Announce Type: new Abstract: The situated view of cognition holds that intelligent behavior depends not only on internal memory, but on an agent's active use of environmental resour…

arXiv AI Read →
◬ AI & Machine Learning Apr 13, 2026
Model Space Reasoning as Search in Feedback Space for Planning Domain Generation

arXiv:2604.08712v1 Announce Type: new Abstract: The generation of planning domains from natural language descriptions remains an open problem even with the advent of large language models and reasonin…

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◬ AI & Machine Learning Apr 13, 2026
Parameterized Complexity Of Representing Models Of MSO Formulas

arXiv:2604.08707v1 Announce Type: new Abstract: Monadic second order logic (MSO2) plays an important role in parameterized complexity due to the Courcelle's theorem. This theorem states that the probl…

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◬ AI & Machine Learning Apr 13, 2026
RAMP: Hybrid DRL for Online Learning of Numeric Action Models

arXiv:2604.08685v1 Announce Type: new Abstract: Automated planning algorithms require an action model specifying the preconditions and effects of each action, but obtaining such a model is often hard.…

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◬ AI & Machine Learning Apr 13, 2026
Sustained Impact of Agentic Personalisation in Marketing: A Longitudinal Case Study

arXiv:2604.08621v1 Announce Type: new Abstract: In consumer applications, Customer Relationship Management (CRM) has traditionally relied on the manual optimisation of static, rule-based messaging str…

arXiv AI Read →
◬ AI & Machine Learning Apr 13, 2026
From Business Events to Auditable Decisions: Ontology-Governed Graph Simulation for Enterprise AI

arXiv:2604.08603v1 Announce Type: new Abstract: Existing LLM-based agent systems share a common architectural failure: they answer from the unrestricted knowledge space without first simulating how ac…

arXiv AI Read →
◬ AI & Machine Learning Apr 13, 2026
OpenKedge: Governing Agentic Mutation with Execution-Bound Safety and Evidence Chains

arXiv:2604.08601v1 Announce Type: new Abstract: The rise of autonomous AI agents exposes a fundamental flaw in API-centric architectures: probabilistic systems directly execute state mutations without…

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◬ AI & Machine Learning Apr 13, 2026
Proving Circuit Functional Equivalence in Zero Knowledge

arXiv:2601.11173v2 Announce Type: replace Abstract: The modern integrated circuit ecosystem is increasingly reliant on third-party intellectual property integration, which introduces security risks, i…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
Reasoning Hijacking: Subverting LLM Classification via Decision-Criteria Injection

arXiv:2601.10294v3 Announce Type: replace Abstract: Current LLM safety research predominantly focuses on mitigating Goal Hijacking, preventing attackers from redirecting a model's high-level objective…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
Towards a Systematic Taxonomy of Attacks against Space Infrastructures

arXiv:2512.12829v2 Announce Type: replace Abstract: Space infrastructures represent an emerging domain that is critical to the global economy and society. However, this domain is vulnerable to attacks…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
Exploiting Web Search Tools of AI Agents for Data Exfiltration

arXiv:2510.09093v2 Announce Type: replace Abstract: Large language models (LLMs) are now routinely used to autonomously execute complex tasks, from natural language processing to dynamic workflows lik…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
Condense to Conduct and Conduct to Condense

arXiv:2508.21602v3 Announce Type: replace Abstract: In this paper, we present the first explicit examples of low-conductance permutations. The notion of conductance of permutations was introduced by D…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
A Deductive System for Contract Satisfaction Proofs

arXiv:2604.09165v1 Announce Type: cross Abstract: Hardware-software contracts are abstract specifications of a CPU's leakage behavior. They enable verifying the security of high-level programs against…

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◬ AI & Machine Learning Apr 13, 2026
DeepGuard: Secure Code Generation via Multi-Layer Semantic Aggregation

arXiv:2604.09089v1 Announce Type: cross Abstract: Large Language Models (LLMs) for code generation can replicate insecure patterns from their training data. To mitigate this, a common strategy for sec…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
Leave My Images Alone: Preventing Multi-Modal Large Language Models from Analyzing Images via Visual Prompt Injection

arXiv:2604.09024v1 Announce Type: cross Abstract: Multi-modal large language models (MLLMs) have emerged as powerful tools for analyzing Internet-scale image data, offering significant benefits but al…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
Joint Interference Detection and Identification via Adversarial Multi-task Learning

arXiv:2604.08607v1 Announce Type: cross Abstract: Precise interference detection and identification are crucial for enhancing the survivability of communication systems in non-cooperative wireless env…

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◬ AI & Machine Learning Apr 13, 2026
Trans-RAG: Query-Centric Vector Transformation for Secure Cross-Organizational Retrieval

arXiv:2604.09541v1 Announce Type: new Abstract: Retrieval Augmented Generation (RAG) systems deployed across organizational boundaries face fundamental tensions between security, accuracy, and efficie…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
XFED: Non-Collusive Model Poisoning Attack Against Byzantine-Robust Federated Classifiers

arXiv:2604.09489v1 Announce Type: new Abstract: Model poisoning attacks pose a significant security threat to Federated Learning (FL). Most existing model poisoning attacks rely on collusion, requirin…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
BadSkill: Backdoor Attacks on Agent Skills via Model-in-Skill Poisoning

arXiv:2604.09378v1 Announce Type: new Abstract: Agent ecosystems increasingly rely on installable skills to extend functionality, and some skills bundle learned model artifacts as part of their execut…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
ChatGPT, is this real? The influence of generative AI on writing style in top-tier cybersecurity papers

arXiv:2604.09316v1 Announce Type: new Abstract: With the release of ChatGPT in 2022, generative AI has significantly lowered the cost of polishing and rewriting text. Due to its widespread usage, conf…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
Cross-Paradigm Models of Restricted Syndrome Decoding with Application to CROSS

arXiv:2604.09292v1 Announce Type: new Abstract: Restricted Syndrome Decoding (ResSD) is a variant of linear code decoding problem where each of the error's entries must belong to a fixed small set of …

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◬ AI & Machine Learning Apr 13, 2026
Unreal Thinking: Chain-of-Thought Hijacking via Two-stage Backdoor

arXiv:2604.09235v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in settings where Chain-of-Thought (CoT) is interpreted by users. This creates a new safety risk:…

arXiv Security Read →
◬ AI & Machine Learning Apr 13, 2026
Hagenberg Risk Management Process (Part 3): Operationalization, Probabilities, and Causal Analysis

arXiv:2604.09153v1 Announce Type: new Abstract: For risks that cannot be accepted, sufficiently mitigated, or eliminated, continuous observation is a viable approach but requires a model that can be o…

arXiv Security Read →
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