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◬ AI & Machine Learning Jun 09, 2026
Beyond Goodhart's Law: A Dynamic Benchmark for Evaluating Compliance in Multi-Agent Systems

arXiv:2606.07805v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) from passive assistants to autonomous, execution-capable agents has introduced critical operational …

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
Improving Multimodal Reasoning via Worst Dimension Optimization

arXiv:2606.07801v1 Announce Type: new Abstract: Multimodal reasoning requires a path that retains integrity over a wide range of constraints, from visual grounding to logic consistency. However, the c…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
Reconstructing and forecasting disease trajectories of patients with Alzheimer's disease using routine data in resource-constrained settings

arXiv:2606.07798v1 Announce Type: new Abstract: Alzheimer's disease is a progressive neurodegenerative disorder, and its progression varies substantially across patients. Existing work aims to forecas…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
Land cover and flood type govern the detection limits of satellite-based flood mapping across diverse global flood events

arXiv:2606.07780v1 Announce Type: new Abstract: Floods are among the most destructive natural hazards, and their increasing frequency under climate change makes satellite-based inundation mapping esse…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
Some hypotheses on how chatbots work in problem-solving-driven conversations. Large Language Models as confirmation of the Innovation Illusion

arXiv:2606.07722v1 Announce Type: new Abstract: This article offers a perspective on the nature of chatbots as genuine conversation partners when discussing problems in relation to their solutions. Wh…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
Automatic Extraction of Structured Information from Brain MRI Reports Using an Open-Weight Large Language Model

arXiv:2606.07721v1 Announce Type: new Abstract: Objectives: Automatic data extraction from free-text radiology reports enables large-scale research, but few studies assessed the performance of large l…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
Why Limit the Residual Stream to Layers and Not Tokens? Persistent Memory for Continuous Latent Reasoning

arXiv:2606.07720v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable reasoning abilities on mathematical and multi-hop planning tasks. The CoCoNuT (Chain of Contin…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
A case study of evaluating AI agents on a neuroscience data-to-discovery pipeline

arXiv:2606.07718v1 Announce Type: new Abstract: Agentic AI tools offer a promising path to automating software development bottlenecks in scientific research pipelines, particularly for stages that ta…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
Syll: Open-Source Personal Automation with Cross-Surface Execution

arXiv:2606.07594v1 Announce Type: new Abstract: Personal AI agents must increasingly operate across APIs, shells, web surfaces, and desktop GUIs, yet many systems remain tuned to a single interface an…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
OmniMem: Perturbation-aware Memory Compression for Streaming Audio-Visual LLMs

arXiv:2606.07577v1 Announce Type: new Abstract: Audio-visual large language models (LLMs) hold strong promise for long-form video understanding, yet their long-video inference is fundamentally limited…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow

arXiv:2606.07549v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) and agent workflows have shown strong promise for computational pathology, yet reliable patc…

arXiv AI Read →
◬ AI & Machine Learning Jun 09, 2026
Sample-Efficient LLM-Based Detection of Malicious Web Server Logs with Forensically Explainable Reasoning

arXiv:2606.08649v1 Announce Type: new Abstract: Forensic analysis of web server logs demands both accurate detection and human-readable explanations that can satisfy legal requirements. We present CEF…

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
Exploring CKKS Parameter Trade-offs for Privacy-Preserving Personalized Federated Learning

arXiv:2606.08521v1 Announce Type: new Abstract: Privacy-preserving Personalized Federated Learning (PFL) enables clients to collaboratively train personalized models without exposing raw data, but exc…

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
Digital White Spaces: A Cyberpsychology-Informed Framework to Mobile Phone Addiction

arXiv:2606.08472v1 Announce Type: new Abstract: Mobile-phone overuse and attention fragmentation have become pressing societal and public-health concerns. Cyberpsychology research highlights addictive…

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◬ AI & Machine Learning Jun 09, 2026
AI Code Sandboxes: A Comparative Security Study. Part 1 of 2 -- Engine-Level Properties (Attack Surface, Leakage, Stackability, CVE History, Patch Cadence, Fuzzing)

arXiv:2606.08433v1 Announce Type: new Abstract: This paper reads six engine-level measurements together -- 1.1 host attack surface, 1.2 information leakage, 1.3 defense-in-depth stackability, 1.4 publ…

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
Hiding in Plain Floats: Steganographic Carriers for Indirect Prompt and Content Injection

arXiv:2606.08403v1 Announce Type: new Abstract: Text-centered prompt-injection defenses assume that the malicious signal is visible in one of the inspected text views. We study a reproducible LLM01-st…

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
SoK: Reconstruction Attacks on Synthetic Tabular Data (Insights from Winning the NIST CRC)

arXiv:2606.08372v1 Announce Type: new Abstract: Synthetic data is increasingly promoted as a privacy-preserving substitute for releasing sensitive tabular records, yet its central adversarial threat (…

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response

arXiv:2606.08270v1 Announce Type: new Abstract: University Academic Management Information Systems (ACMIS) are high-value targets for a wide spectrum of security threats including brute-force login at…

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
Quantifying and Defending against the Privacy Risk in Logit-based Federated Learning

arXiv:2606.08252v1 Announce Type: new Abstract: Federated learning aims to protect data privacy by collaboratively learning a model without sharing private data among clients. Unlike traditional param…

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
LPOR: A Layered Proof of Reserves Framework for Usable and Publicly Auditable Solvency Verification

arXiv:2606.08211v1 Announce Type: new Abstract: Proof of Reserves (PoR) enables centralized crypto exchanges to demonstrate that on-chain reserves are sufficient to cover customer liabilities. However…

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
AI-Native Closed-Loop Security for 6G-Enabled Cyber-Physical Systems: From Edge Detection to Network-Wide Mitigation

arXiv:2606.08173v1 Announce Type: new Abstract: In sixth-generation (6G) networks, billions of cyber-physical systems (CPSs) - autonomous vehicles, smart grids, industrial robots, and remote-surgical …

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
Closing the Sim-to-Real Gap: An Evaluation Framework for Autonomous Cyber Defense Configuration of Commercial EDR

arXiv:2606.08168v1 Announce Type: new Abstract: Leading commercial endpoint detection and response (EDR) products have shifted from operator-configured rule sets to multi-component systems where auton…

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
Policy Description Language for Authorization using Logic-Based Programming

arXiv:2606.08119v1 Announce Type: new Abstract: Recently, with the impossibility of eradicating the vulnerabilities of information systems, we must prepare for the occurrence of the security incident …

arXiv Security Read →
◬ AI & Machine Learning Jun 09, 2026
The Dodona Protocol: A Living Design Science Experiment in Oracle Design

arXiv:2606.08012v1 Announce Type: new Abstract: The oracle problem, broadly understood as the difficulty of reliably incorporating external information into blockchain-based systems, has been widely e…

arXiv Security Read →
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