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🔥 Trending Topics · Last 48h
◬ AI & Machine Learning Aug 06, 2026
Adversarially Robust Abductive Fusion of Pre-trained Transformer-based Perception Models

arXiv:2608.04190v1 Announce Type: new Abstract: Deploying pre-trained perception models in novel environments degrades their accuracy under distributional shift, and assembling them alone does not rec…

arXiv AI Read →
◬ AI & Machine Learning Aug 06, 2026
BrainBench: Benchmarking Large Language Models for Comprehensive EEG Understanding

arXiv:2608.04156v1 Announce Type: new Abstract: Electroencephalography (EEG) analysis extends beyond assigning predefined labels to recordings; it requires workflows connecting natural-language instru…

arXiv AI Read →
◬ AI & Machine Learning Aug 06, 2026
FinPerMA: A Theory-Informed, Event-Grounded Personalized-Memory Benchmark for LLM Agents

arXiv:2608.04095v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly used as personalized assistants in high-stakes domains such as financial advising, yet it remains unc…

arXiv AI Read →
◬ AI & Machine Learning Aug 06, 2026
FinProBench: Evaluating Financial AI Agents with Role-Grounded Rubrics Derived from Professional Deliverables

arXiv:2608.04077v1 Announce Type: new Abstract: Evaluating financial AI agents requires criteria aligned with real professional work. Existing rubric methods typically derive criteria from task prompt…

arXiv AI Read →
◬ AI & Machine Learning Aug 06, 2026
Monte Carlo Tree Search for Table-to-Multimodal Report Generation

arXiv:2608.04071v1 Announce Type: new Abstract: Automatically generating professional multimodal reports comprising both textual analysis and visual charts from structured tabular data is a critical c…

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◬ AI & Machine Learning Aug 06, 2026
The LLM Proposes, the Executive Disposes: A Self-Verifying Agent Instrument that Dissociates Commitment Drift from Binding Drift in Long-Horizon Agents

arXiv:2608.04066v1 Announce Type: new Abstract: How do you verify a long-horizon agent when its own state and self-reports are exactly what you cannot trust? We present an agent instrument built so th…

arXiv AI Read →
◬ AI & Machine Learning Aug 06, 2026
A Long-Run Persistence Theory for AI Systems under the Redundancy-Adjusted Artificial Age Score (AAS)

arXiv:2608.04012v1 Announce Type: new Abstract: Artificial intelligence systems are increasingly expected to operate over repeated cycles of interaction, adaptation, and update rather than through iso…

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◬ AI & Machine Learning Aug 06, 2026
HoRFFI: High-Openness RF Fingerprint Identification with a Similarity-Enhanced Variational Information Bottleneck

arXiv:2608.04881v1 Announce Type: new Abstract: Radio frequency fingerprint identification (RFFI) is a promising technique for wireless device authentication. However, practical RFFI systems must enro…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
Hidden Ciphers and Where to Find Them: Static Discovery and Assessment of Cryptographic Assets in Software

arXiv:2608.04857v1 Announce Type: new Abstract: Modern software systems rely on cryptography for data protection, authentication, and trust establishment, yet organizations often lack a structured vie…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
PURPOSE: Poisoning Conflict Resolution in RAG via Proxy-Fact-Grounded Updates

arXiv:2608.04756v1 Announce Type: new Abstract: In Retrieval-Augmented Generation (RAG), post-retrieval conflict resolution arbitrates among noisy or contradictory retrieved passages. However, the rob…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
"Allow" to Achieve, Over-Privileged Inadvertently: The Unintended Cost of Task-Completion-Driven Pop-up Decisions in Mobile GUI Agents

arXiv:2608.04755v1 Announce Type: new Abstract: Mobile GUI agents routinely encounter system permission dialogs during task execution, yet their ability to grant only permissions that are necessary fo…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
Web Cache Overflow: Exploiting Imprecise Keys for Cache Degradation and Beyond

arXiv:2608.04744v1 Announce Type: new Abstract: Web caches support the scalability needs of contemporary web applications by storing frequently accessed objects closer to clients. Web caches are conce…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
LoginTrap: Uncovering Task-Agnostic Phishing-Style Indirect Prompt Injection Attacks against LLM-based Web Agents

arXiv:2608.04741v1 Announce Type: new Abstract: LLM-based web agents automate user tasks by observing webpages and executing browser actions on behalf of users. As these agents operate on real web ser…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs

arXiv:2608.04680v1 Announce Type: new Abstract: To adopt the Vision Transformers (ViTs) in resource-constrained environment, token pruning is widely used to reduce computational cost without impacting…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
Blockchain Empowered Trustworthy Agent Networks: Foundations, Taxonomy, and Future Directions

arXiv:2608.04626v1 Announce Type: new Abstract: AI agents are evolving from isolated task executors into networked autonomous entities that can communicate, delegate tasks, invoke tools, access extern…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
Adaptive Intrusion Detection System using Transformer-Based Neural Networks and Continual Learning Approach with Adversarial Investigation

arXiv:2608.04602v1 Announce Type: new Abstract: Network intrusion detection systems (IDS) trained on fixed traffic snapshots decay silently after deployment as threat distributions shift. Fine-tuning …

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
Breadcrumbing Search Agents

arXiv:2608.04565v1 Announce Type: new Abstract: LLM-based search agents are widely used for information-seeking tasks, but their reliance on external tool returns introduces a critical security risk: …

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
Checked-In Secret Detection: Strings Are All You Need

arXiv:2608.04523v1 Announce Type: new Abstract: Hardcoded secrets in source code pose critical security vulnerabilities which can be easily exploited by malicious adversaries. Existing regex-based det…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
DeepInvert: Semi-Supervised Embedding Inversion Against Obfuscated Language Models

arXiv:2608.04477v1 Announce Type: new Abstract: Cloud-based language model services routinely process prompts containing sensitive information. Obfuscation-based defenses---including ObfusLM, Sentinel…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
Large Language Models and Social Media Information Integrity: Opportunities, Challenges, and Research Directions

arXiv:2608.04375v1 Announce Type: new Abstract: Large Language Models (LLMs) have emerged as powerful tools that impact information integrity on social media platforms. This comprehensive review exami…

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◬ AI & Machine Learning Aug 06, 2026
Combating Knowledge Corruption in Agent Systems: A Byzantine-Tolerant Secure Collaborative RAG Framework

arXiv:2608.04366v1 Announce Type: new Abstract: While retrieval-augmented generation systems partially address the hallucination issues in large language models, it also introduces new vulnerabilities…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
Trident : How to Break Deep Reinforcement Learning Cyber Defenses (Agentic)

arXiv:2608.04317v1 Announce Type: new Abstract: Autonomous cyber defense systems based on Deep Reinforcement Learning (DRL) have attracted significant research attention, yet remain evaluated almost e…

arXiv Security Read →
◬ AI & Machine Learning Aug 06, 2026
Adversarial Attacks for Good: A Survey of Proactive Protection across the Visual Content Lifecycle

arXiv:2608.04314v1 Announce Type: new Abstract: Once visual content enters an AI pipeline, its owner often retains little technical control over how it is used. Legal and regulatory remedies can addre…

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◬ AI & Machine Learning Aug 06, 2026
PriDyG: Privacy-preserving Dynamic Graph Inference with LLM-GNN Collaboration

arXiv:2608.04255v1 Announce Type: new Abstract: Graph inference over relational data can expose sensitive edge information, and this risk becomes more severe in dynamic graphs, where repeated model up…

arXiv Security Read →
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