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◬ AI & Machine Learning May 25, 2026
EVE-Agent: Evidence-Verifiable Self-Evolving Agents

arXiv:2605.22905v1 Announce Type: new Abstract: Self-evolving agents should not train on examples they cannot justify. Data-free self-evolving search agents offer a scalable route to systems that gene…

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◬ AI & Machine Learning May 25, 2026
Mediative Fuzzy Logic: From Type-1 Foundations to Type-2, Type-3 and Quantum Extensions

arXiv:2605.22900v1 Announce Type: new Abstract: Mediative Fuzzy Logic was conceived as a practical scheme for reconciling hesitant or conflicting assessments in fuzzy control and decision-making. Howe…

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◬ AI & Machine Learning May 25, 2026
ImProver 2: Iteratively Self-Improving LMs for Neurosymbolic Proof Optimization

arXiv:2605.22885v1 Announce Type: new Abstract: Formal mathematics libraries are rapidly expanding, creating a growing need to refactor verified proofs for maintainability and to improve training data…

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◬ AI & Machine Learning May 25, 2026
Energy per Successful Goal: Goal-Level Energy Accounting for Agentic AI Systems

arXiv:2605.22883v1 Announce Type: new Abstract: Current AI energy benchmarks measure consumption at the granularity of a single model invocation or training run. For classical single-turn workloads th…

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◬ AI & Machine Learning May 25, 2026
SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research

arXiv:2605.22878v1 Announce Type: new Abstract: The exponential growth of global academic output has confronted researchers and AI agents with an unprecedented ``information explosion,'' where fragmen…

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◬ AI & Machine Learning May 25, 2026
RMA: an Agentic System for Research-Level Mathematical Problems

arXiv:2605.22875v1 Announce Type: new Abstract: We present $\textbf{Research Math Agents (RMA)}$, an agentic framework for automated reasoning on research-level mathematical problems. Unlike prior stu…

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◬ AI & Machine Learning May 25, 2026
NeuroNL2LTL: A Neurosymbolic Framework for Natural Language Translation of Linear Temporal Logic

arXiv:2605.22874v1 Announce Type: new Abstract: Effectively translating between natural language (NL) and formal logics like Linear Temporal Logic (LTL) requires expertise that limits formal verificat…

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◬ AI & Machine Learning May 25, 2026
BOHM: Zero-Cost Hierarchical Attribution for Compound AI Systems

arXiv:2605.22866v1 Announce Type: new Abstract: Compound AI systems route tasks through hierarchies of specialised components. Attribution is dominated by Shapley-based methods (SHAP), which decompose…

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◬ AI & Machine Learning May 25, 2026
A Commitment-based Authentication model for Key Exchange protocols

arXiv:2307.15465v4 Announce Type: replace Abstract: In this work we construct an alternative model for Authenticated Key Exchange, intended to build a theoretic security framework for protocols whose …

arXiv Security Read →
◬ AI & Machine Learning May 25, 2026
CHRONOS: Temporally-Aware Multi-Agent Coordination for Evolving Data Marketplaces

arXiv:2605.23887v1 Announce Type: cross Abstract: Temporal knowledge-graph data marketplaces face three coupled failures in static designs: stale hybrid index shortcuts reduce recall as edges evolve, …

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◬ AI & Machine Learning May 25, 2026
On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy

arXiv:2605.23879v1 Announce Type: cross Abstract: Gradient-flow sampling interprets a Gibbs distribution as the minimizer of an energy functional over probability measures and generates dynamics conve…

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◬ AI & Machine Learning May 25, 2026
Communication Security and Sensing Privacy in FMCW-Based ISAC Through Signal Modulation

arXiv:2605.23429v1 Announce Type: cross Abstract: This study proposes a novel radar-centric signaling design and architecture for secure integrated sensing and communication (ISAC) systems. The propos…

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◬ AI & Machine Learning May 25, 2026
Sample-wise Targeted Adversarial Attacks on Test-time Adaptation

arXiv:2605.23411v1 Announce Type: cross Abstract: Test-time adaptation (TTA) effectively counters distribution shifts but exposes models to adversarial manipulation via the unlabeled test stream. Exis…

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◬ AI & Machine Learning May 25, 2026
Formal Verification of Probing Security via Conditional Independence

arXiv:2605.23316v1 Announce Type: cross Abstract: Side-channel attacks are a major threat to the security of cryptosystems. Masking is a widely used countermeasure against such attacks, but proving th…

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◬ AI & Machine Learning May 25, 2026
On APN Exponents and the Differential and Boomerang Properties of Binomials in Characteristic 3

arXiv:2605.23224v1 Announce Type: cross Abstract: Recent studies on binomials of the form $F_r(x) = x^r(1 + \chi(x))$ over $\mathbb{F}_{p^n}$ have shown that these functions can exhibit very low boome…

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◬ AI & Machine Learning May 25, 2026
From Preventive to Reactive: How AI Coding Assistants Transform Developers' Security Awareness

arXiv:2605.23130v1 Announce Type: cross Abstract: AI coding assistants are now central to professional software development, yet their impact on how developers think about and practice security remain…

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◬ AI & Machine Learning May 25, 2026
Security of LLM-generated Code: A Comparative Analysis

arXiv:2605.23091v1 Announce Type: cross Abstract: The majority of software developers use or are planning to use Artificial Intelligence (AI) tools in their development processes. Their top reasons in…

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◬ AI & Machine Learning May 25, 2026
Intercloud: Eventual Consistency for Decentralised Economies via Chilling-Effect Consensus

arXiv:2605.22830v1 Announce Type: cross Abstract: We present Intercloud, a decentralised economic network in which streams of private data are secured by Watcher swarms that observe only cryptographic…

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◬ AI & Machine Learning May 25, 2026
Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Token

arXiv:2605.20192v1 Announce Type: cross Abstract: Decentraland, a decentralized virtual reality platform operating within the expanding Metaverse ecosystem, utilizes its native MANA token to facilitat…

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◬ AI & Machine Learning May 25, 2026
A blueprint for constructing 3-pass AKE protocols under commitment-based models

arXiv:2605.23843v1 Announce Type: new Abstract: The commitment-based AKE model provides a formal security framework for key exchange protocols that avoid long-term cryptographic material, achieving au…

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◬ AI & Machine Learning May 25, 2026
Validating Threat Modeling Results with the Help of Vulnerable Test Applications

arXiv:2605.23695v1 Announce Type: new Abstract: Validating threat modeling results remains difficult because completeness is hard to judge without an external oracle. Existing studies often rely on ex…

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◬ AI & Machine Learning May 25, 2026
Less Effort, Shorter Proofs: Reinforcement Learning for Security Protocol Analysis in Tamarin

arXiv:2605.23643v1 Announce Type: new Abstract: Tools like Tamarin and ProVerif have achieved notable success in analyzing and verifying complex real-world protocols such as EMV, 5G, and WPA2, even de…

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◬ AI & Machine Learning May 25, 2026
Kernel-Based ReLU Approximation for Homomorphic Encryption-Compatible Privacy-preserving Deep Learning Models

arXiv:2605.23641v1 Announce Type: new Abstract: As privacy concerns in AI technologies continue to grow, Homomorphic Encryption (HE) offers a way to perform computations on encrypted data without the …

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◬ AI & Machine Learning May 25, 2026
CachePrune: Privacy-Aware and Fine-Grained KV Cache Sharing for Efficient LLM Inference

arXiv:2605.23640v1 Announce Type: new Abstract: Large Language Models (LLMs) rely on Key-Value (KV) caching to accelerate inference, and many serving systems further share the KV cache across users' r…

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