CyberIntel ⬡ News
★ Saved ◆ Cyber Reads

// Cyber
Intel Feed

cyberintel.kalymoon.com  ·  20466 articles  ·  updated every 4 hours · grows forever

20466Total
17906Full Text
May 16, 2026Latest
◈ Women in Cyber ◉ Threat Intelligence ◎ How-To & Tutorials ⬡ Vulnerabilities & CVEs 🔍 Digital Forensics ◍ Incident Response & DFIR ◆ Security Tools & Reviews ◇ Industry News & Leadership ✉ Email Security 🛡 Active Threats ⚠ Critical CVEs ◐ Insider Threat & DLP ◌ Quantum Computing ◬ AI & Machine Learning
🔥 Trending Topics · Last 48h
◇ Industry News & Leadership May 15, 2026
Bypassing On-Camera Age-Verification Checks

Some AI-based video age-verification checks can be fooled with a fake mustache .

Schneier on Security Read →
🛡 Active Threats May 15, 2026
No need to hack when it’s leaking: Dalbir Singh & Associates law firm edition

Dalbir Singh & Associates ignored multiple attempts at responsible disclosure but finally locked down its misconfigured Amazon bucket, only to expose it again. Now the data is in the hands of criminal…

DataBreaches.net Read →
◬ AI & Machine Learning May 15, 2026
GenCircuit-RL: Reinforcement Learning from Hierarchical Verification for Genetic Circuit Design

arXiv:2605.14215v1 Announce Type: new Abstract: Genetic circuit design remains a laborious, expert-driven process despite decades of progress in synthetic biology. We study this problem through code g…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
MetaAgent-X : Breaking the Ceiling of Automatic Multi-Agent Systems via End-to-End Reinforcement Learning

arXiv:2605.14212v1 Announce Type: new Abstract: Automatic multi-agent systems aim to instantiate agent workflows without relying on manually designed or fixed orchestration. However, existing automati…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
ASH: Agents that Self-Hone via Embodied Learning

arXiv:2605.14211v1 Announce Type: new Abstract: Long-horizon embodied tasks remain a fundamental challenge in AI, as current methods rely on hand-engineered rewards or action-labeled demonstrations, n…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
SimPersona: Learning Discrete Buyer Personas from Raw Clickstreams for Grounded E-Commerce Agents

arXiv:2605.14205v1 Announce Type: new Abstract: LLM-based web agents can navigate live storefronts, yet they often collapse to a single "average buyer" policy, failing to capture the heterogeneous and…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Grounded Continuation: A Linear-Time Runtime Verifier for LLM Conversations

arXiv:2605.14175v1 Announce Type: new Abstract: In long conversations, an LLM can produce a next utterance that sounds plausible but rests on premises the conversation has already abandoned. Context-m…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
The Evaluation Trap: Benchmark Design as Theoretical Commitment

arXiv:2605.14167v1 Announce Type: new Abstract: Every AI benchmark operationalizes theoretical assumptions about the capability it claims to assess. When assumptions function as unexamined commitments…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Unsteady Metrics and Benchmarking Cultures of AI Model Builders

arXiv:2605.14164v1 Announce Type: new Abstract: The primary way to establish and compare competencies in foundation and generative AI models has shifted from peer-reviewed literature to press releases…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Agentic Systems as Boosting Weak Reasoning Models

arXiv:2605.14163v1 Announce Type: new Abstract: Can a committee of weak reasoning-model calls reach the performance of much stronger models? We study verifier-backed committee search as inference-time…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Distribution-Aware Algorithm Design with LLM Agents

arXiv:2605.14141v1 Announce Type: new Abstract: We study learning when the learned object is executable solver code rather than a predictor. In this setting, correctness is not enough: two solvers may…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
ClawForge: Generating Executable Interactive Benchmarks for Command-Line Agents

arXiv:2605.14133v1 Announce Type: new Abstract: Interactive agent benchmarks face a tension between scalable construction and realistic workflow evaluation. Hand-authored tasks are expensive to extend…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Modeling Bounded Rationality in Drug Shortage Pharmacists Using Attention-Guided Dynamic Decomposition

arXiv:2605.14111v1 Announce Type: new Abstract: Hospital pharmacists make high-stakes decisions to mitigate drug shortages under uncertainty, time pressure, and patient risk. Interviews revealed that …

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
ChromaFlow: A Negative Ablation Study of Orchestration Overhead in Tool-Augmented Agent Evaluation

arXiv:2605.14102v1 Announce Type: new Abstract: Autonomous language-model agents increasingly combine planning, tool use, document processing, browsing, code execution, and verification loops. These c…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
SkillFlow: Flow-Driven Recursive Skill Evolution for Agentic Orchestration

arXiv:2605.14089v1 Announce Type: new Abstract: In recent years, a variety of powerful LLM-based agentic systems have been applied to automate complex tasks through task orchestration. However, existi…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Know When To Fold 'Em: Token-Efficient LLM Synthetic Data Generation via Multi-Stage In-Flight Rejection

arXiv:2605.14062v1 Announce Type: new Abstract: While synthetic data generation with large language models (LLMs) is widely used in post-training pipelines, existing approaches typically generate full…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
MathAtlas: A Benchmark for Autoformalization in the Wild

arXiv:2605.14061v1 Announce Type: new Abstract: Current autoformalization benchmarks are largely focused on olympiad or undergraduate mathematics, while graduate and research-level mathematics remains…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Bad Seeing or Bad Thinking? Rewarding Perception for Vision-Language Reasoning

arXiv:2605.14054v1 Announce Type: new Abstract: Achieving robust perception-reasoning synergy is a central goal for advanced Vision-Language Models (VLMs). Recent advancements have pursued this goal v…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
SPIN: Structural LLM Planning via Iterative Navigation for Industrial Tasks

arXiv:2605.14051v1 Announce Type: new Abstract: Industrial LLM agent systems often separate planning from execution, yet LLM planners frequently produce structurally invalid or unnecessarily long work…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Bridging Legal Interpretation and Formal Logic: Faithfulness, Assumption, and the Future of AI Legal Reasoning

arXiv:2605.14049v1 Announce Type: new Abstract: The growing adoption of large language models in legal practice brings both significant promise and serious risk. Legal professionals stand to benefit f…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Network-Aware Bilinear Tokenization for Brain Functional Connectivity Representation Learning

arXiv:2605.14048v1 Announce Type: new Abstract: Masked autoencoders (MAEs) have recently shown promise for self-supervised representation learning of resting-state brain functional connectivity (FC). …

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Model-Adaptive Tool Necessity Reveals the Knowing-Doing Gap in LLM Tool Use

arXiv:2605.14038v1 Announce Type: new Abstract: Large language models (LLMs) increasingly act as autonomous agents that must decide when to answer directly vs. when to invoke external tools. Prior wor…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
Enhanced and Efficient Reasoning in Large Learning Models

arXiv:2605.14036v1 Announce Type: new Abstract: In current Large Language Models we can trust the production of smoothly flowing prose on the basis of the principles of machine learning. However, ther…

arXiv AI Read →
◬ AI & Machine Learning May 15, 2026
From Descriptive to Prescriptive: Uncover the Social Value Alignment of LLM-based Agents

arXiv:2605.14034v1 Announce Type: new Abstract: Wide applications of LLM-based agents require strong alignment with human social values. However, current works still exhibit deficiencies in self-cogni…

arXiv AI Read →
← Prev 8 / 853 Next →