AppSentinels Named Leader and Outperformer in GigaOm Radar for API Security
AppSentinels, leader in Business Logic Security for APIs, AI Agents, and MCP workflows, today announced that it has been recognized as a Leader and Outperformer in the GigaOm Radar for API Security. The GigaOm Radar evaluates leading API security vendors across key capabilities such as discovery, te...
Pondurance Announced the Launch of Pondurance Kanati(™)
Pondurance’s Agentic AI and platform delivers rapid threat containment, 95% faster response times, and 80% reduction in false positive tickets — fundamentally redefining the economics and performance of managed security operations Pondurance, the leading provider of next-generation managed detection...
Neon Cyber, SpyCloud Partner to Deliver Identity Intelligence at Scale
Strategic partnership brings urgent identity threat visibility context to help businesses prevent credential-stuffing attacks Neon Cyber, innovators of the first security platform purpose-built to protect the way modern teams work, today announced a strategic partnership with SpyCloud, the leader in...
Mistral Small 4: The One Model That Codes, Reasons, and Chats
Artificial intelligence is rapidly evolving. New models emerge nearly every day, with each one attempting to be the best. In this sea of similar models, we see something new every now and then. One of such models is the new Mistral Small 4. It is an innovative AI model that is not only going to […]
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Advancing Open Source AI, NVIDIA Donates Dynamic Resource Allocation Driver for GPUs to Kubernetes Community
Artificial intelligence has rapidly emerged as one of the most critical workloads in modern computing. For the vast majority of enterprises, this workload runs on Kubernetes, an open source platform that automates the deployment, scaling and management of containerized applications. To help the glob...
XBOW Embeds AI Penetration Testing in Microsoft Security
Integration with Microsoft Security Copilot and Microsoft Sentinel Data Lake Unifies AppSec and SecOps Through Autonomous Offensive Security XBOW, a leading autonomous offensive security company, today announced a new collaboration with Microsoft, integrating XBOW’s continuous penetration testing pl...
Rootstock Software Announced the Acquisition of Ascent Solutions
Acquisition allows Rootstock to deepen its Salesforce-native ERP and operational capabilities for manufacturers and distributors Rootstock Software (“Rootstock” or “the Company”), a recognized leader in cloud ERP for product-based companies, today announced its acquisition of Ascent Solutions (“Asce...
Yann LeCun’s New LeWorldModel (LeWM) Research Targets JEPA Collapse in Pixel-Based Predictive World Modeling
World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However, training these models directly from pixel data often leads to ‘representation collapse,’ where the model produces redundant embeddings to trivially satisfy prediction objectives....
AgenticGEO: A Self-Evolving Agentic System for Generative Engine Optimization
arXiv:2603.20213v1 Announce Type: new
Abstract: Generative search engines represent a transition from traditional ranking-based retrieval to Large Language Model (LLM)-based synthesis, transforming optimization goals from ranking prominence towards content inclusion. Generative Engine Optimization ...
ProMAS: Proactive Error Forecasting for Multi-Agent Systems Using Markov Transition Dynamics
arXiv:2603.20260v1 Announce Type: new
Abstract: The integration of Large Language Models into Multi-Agent Systems (MAS) has enabled the so-lution of complex, long-horizon tasks through collaborative reasoning. However, this collec-tive intelligence is inherently fragile, as a single logical fallacy...
Domain-Specialized Tree of Thought through Plug-and-Play Predictors
arXiv:2603.20267v1 Announce Type: new
Abstract: While Large Language Models (LLMs) have advanced complex reasoning, prominent methods like the Tree of Thoughts (ToT) framework face a critical trade-off between exploration depth and computational efficiency. Existing ToT implementations often rely o...
FactorSmith: Agentic Simulation Generation via Markov Decision Process Decomposition with Planner-Designer-Critic Refinement
arXiv:2603.20270v1 Announce Type: new
Abstract: Generating executable simulations from natural language specifications remains a challenging problem due to the limited reasoning capacity of large language models (LLMs) when confronted with large, interconnected codebases. This paper presents Factor...
Me, Myself, and $\pi$ : Evaluating and Explaining LLM Introspection
arXiv:2603.20276v1 Announce Type: new
Abstract: A hallmark of human intelligence is Introspection-the ability to assess and reason about one's own cognitive processes. Introspection has emerged as a promising but contested capability in large language models (LLMs). However, current evaluations oft...
JointFM-0.1: A Foundation Model for Multi-Target Joint Distributional Prediction
arXiv:2603.20266v1 Announce Type: new
Abstract: Despite the rapid advancements in Artificial Intelligence (AI), Stochastic Differential Equations (SDEs) remain the gold-standard formalism for modeling systems under uncertainty. However, applying SDEs in practice is fraught with challenges: modeling...
MARLIN: Multi-Agent Reinforcement Learning for Incremental DAG Discovery
arXiv:2603.20295v1 Announce Type: new
Abstract: Uncovering causal structures from observational data is crucial for understanding complex systems and making informed decisions. While reinforcement learning (RL) has shown promise in identifying these structures in the form of a directed acyclic grap...
Collaborative Adaptive Curriculum for Progressive Knowledge Distillation
arXiv:2603.20296v1 Announce Type: new
Abstract: Recent advances in collaborative knowledge distillation have demonstrated cutting-edge performance for resource-constrained distributed multimedia learning scenarios. However, achieving such competitiveness requires addressing a fundamental mismatch: ...
Rolling-Origin Validation Reverses Model Rankings in Multi-Step PM10 Forecasting: XGBoost, SARIMA, and Persistence
arXiv:2603.20315v1 Announce Type: new
Abstract: (a) Many air quality forecasting studies report gains from machine learning, but evaluations often use static chronological splits and omit persistence baselines, so the operational added value under routine updating is unclear.
(b) Using 2,350 dail...
Meta AI’s New Hyperagents Don’t Just Solve Tasks—They Rewrite the Rules of How They Learn
The dream of recursive self-improvement in AI—where a system doesn’t just get better at a task, but gets better at learning—has long been the ‘holy grail’ of the field. While theoretical models like the Gödel Machine have existed for decades, they remained largely impractical in real-world settings....
Luma Labs Launches Uni-1: The Autoregressive Transformer Model that Reasons through Intentions Before Generating Images
In the field of generative AI media, the industry is transitioning from purely probabilistic pixel synthesis toward models capable of structural reasoning. Luma Labs has just released Uni-1, a foundational image model designed to address the ‘intent gap” inherent in standard diffusion pipelines. By ...
Trained on Tokens, Calibrated on Concepts: The Emergence of Semantic Calibration in LLMs
Large Language Models (LLMs) often lack meaningful confidence estimates for their outputs. While base LLMs are known to exhibit next-token calibration, it remains unclear whether they can assess confidence in the actual meaning of their responses beyond the token level. We find that, when using a ce...
Scaling Synthetic Task Generation for Agents via Exploration
Post-Training Multimodal Large Language Models (MLLMs) to build interactive agents holds promise across domains such as computer-use, web navigation, and robotics. A key challenge in scaling such post-training is lack of high-quality downstream agentic task datasets with tasks that are diverse, feas...