arXiv:2609.08015v1 Announce Type: new Abstract: Long-running AI agents may read state, reason, wait for tools or human approval, and perform an external…
Author: script
Eliciting Self-Verification in Multimodal Reasoning Agents with Reinforcement Learning
arXiv:2609.08025v1 Announce Type: new Abstract: Reasoning agents increasingly rely on external tools such as web search to answer complex queries.…
Supply chains detect fast, act slow: How AI agents fix it
Supply chain disruption cost businesses about $184 billion in 2025, according to the J.S. Held Global Risk Report, and most of that bill still buys faster…
Sparks of In Silico Cognitive Science: Theories from Simulated Data Can Generalize to Humans
arXiv:2609.08003v1 Announce Type: new Abstract: Behavioral foundation models have been proposed as stand-ins for human participants across settings, but…
NVIDIA Details Skild AI Collaboration Behind S1 Robot Foundation Model
NVIDIA on September 10, 2026 detailed how Skild AI built its S1 robot foundation model on NVIDIA AI infrastructure, and said the robotics company reached…
ResidualAuth: What Authorization State Must Language Agents Preserve under Revocable Delegation?
arXiv:2609.08062v1 Announce Type: new Abstract: Tool-using language agents can delegate and revoke permissions while acting through external services. We…
AI News Brief Hourly Summary 2026-09-10 19h : 24 posts
24 posts published in the last hour 16:34Abacus.AI Releases Three Open-Weight Smaug Models for Agentic Workloads 16:34Feature Engineering in Scikit-Learn: A KDnuggets Cheat Sheet 16:34Mini-Batch Risk-Averse Deep Q-Learning: A Robot Navigation Case Study 16:34Build an end-to-end RFI questionnaire workflow using…
Abacus.AI Releases Three Open-Weight Smaug Models for Agentic Workloads
Abacus.AI on September 10, 2026, introduced the Smaug line, three open-weight language models fine-tuned for enterprise agentic workloads: Smaug Agentic,…
Feature Engineering in Scikit-Learn: A KDnuggets Cheat Sheet
Once feature engineering lives inside a Pipeline , each step is fitted on training data only, and the model is scored what it actually earned. And that is…
Mini-Batch Risk-Averse Deep Q-Learning: A Robot Navigation Case Study
arXiv:2609.07998v1 Announce Type: new Abstract: We study the control of Markov decision processes in which the quality of a policy is evaluated by a…