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Overcoming Nonsmoothness and Control Chattering in Nonconvex Optimal Control Problems Towards Data Science

Overcoming Nonsmoothness and Control Chattering in Nonconvex Optimal Control ProblemsTowards Data Science With some hints for good numerics
The post Overcoming Nonsmoothness and Control Chattering in Nonconvex Optimal Control Problems appeared first on Towards Data Science.

 With some hints for good numerics
The post Overcoming Nonsmoothness and Control Chattering in Nonconvex Optimal Control Problems appeared first on Towards Data Science. Read More  

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Alibaba Tongyi Lab Releases MAI-UI: A Foundation GUI Agent Family that Surpasses Gemini 2.5 Pro, Seed1.8 and UI-Tars-2 on Android WorldMarkTechPost

Alibaba Tongyi Lab Releases MAI-UI: A Foundation GUI Agent Family that Surpasses Gemini 2.5 Pro, Seed1.8 and UI-Tars-2 on Android WorldMarkTechPost

Alibaba Tongyi Lab Releases MAI-UI: A Foundation GUI Agent Family that Surpasses Gemini 2.5 Pro, Seed1.8 and UI-Tars-2 on AndroidWorldMarkTechPost Alibaba Tongyi Lab have released MAI-UI—a family of foundation GUI agents. It natively integrates MCP tool use, agent user interaction, device–cloud collaboration, and online RL, establishing state-of-the-art results in general GUI grounding and mobile GUI navigation, surpassing Gemini-2.5-Pro, Seed1.8, and UI-Tars-2 on AndroidWorld. The system targets three specific gaps that early GUI agents often ignore,
The post Alibaba Tongyi Lab Releases MAI-UI: A Foundation GUI Agent Family that Surpasses Gemini 2.5 Pro, Seed1.8 and UI-Tars-2 on AndroidWorld appeared first on MarkTechPost.

 Alibaba Tongyi Lab have released MAI-UI—a family of foundation GUI agents. It natively integrates MCP tool use, agent user interaction, device–cloud collaboration, and online RL, establishing state-of-the-art results in general GUI grounding and mobile GUI navigation, surpassing Gemini-2.5-Pro, Seed1.8, and UI-Tars-2 on AndroidWorld. The system targets three specific gaps that early GUI agents often ignore,
The post Alibaba Tongyi Lab Releases MAI-UI: A Foundation GUI Agent Family that Surpasses Gemini 2.5 Pro, Seed1.8 and UI-Tars-2 on AndroidWorld appeared first on MarkTechPost. Read More  

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CSA Issues Alert on Critical SmarterMail Bug Allowing Remote Code Execution The Hacker Newsinfo@thehackernews.com (The Hacker News)

The Cyber Security Agency of Singapore (CSA) has issued a bulletin warning of a maximum-severity security flaw in SmarterTools SmarterMail email software that could be exploited to achieve remote code execution. The vulnerability, tracked as CVE-2025-52691, carries a CVSS score of 10.0. It relates to a case of arbitrary file upload that could enable code […]

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How to Integrate AI into Modern SOC Workflows The Hacker Newsinfo@thehackernews.com (The Hacker News)

Artificial intelligence (AI) is making its way into security operations quickly, but many practitioners are still struggling to turn early experimentation into consistent operational value. This is because SOCs are adopting AI without an intentional approach to operational integration. Some teams treat it as a shortcut for broken processes. Others attempt to apply machine learning […]

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How to Build a Robust Multi-Agent Pipeline Using CAMEL with Planning, Web-Augmented Reasoning, Critique, and Persistent Memory MarkTechPost

How to Build a Robust Multi-Agent Pipeline Using CAMEL with Planning, Web-Augmented Reasoning, Critique, and Persistent MemoryMarkTechPost In this tutorial, we build an advanced, end-to-end multi-agent research workflow using the CAMEL framework. We design a coordinated society of agents, Planner, Researcher, Writer, Critic, and Finalizer, that collaboratively transform a high-level topic into a polished, evidence-grounded research brief. We securely integrate the OpenAI API, orchestrate agent interactions programmatically, and add lightweight persistent memory
The post How to Build a Robust Multi-Agent Pipeline Using CAMEL with Planning, Web-Augmented Reasoning, Critique, and Persistent Memory appeared first on MarkTechPost.

 In this tutorial, we build an advanced, end-to-end multi-agent research workflow using the CAMEL framework. We design a coordinated society of agents, Planner, Researcher, Writer, Critic, and Finalizer, that collaboratively transform a high-level topic into a polished, evidence-grounded research brief. We securely integrate the OpenAI API, orchestrate agent interactions programmatically, and add lightweight persistent memory
The post How to Build a Robust Multi-Agent Pipeline Using CAMEL with Planning, Web-Augmented Reasoning, Critique, and Persistent Memory appeared first on MarkTechPost. Read More  

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Mustang Panda Uses Signed Kernel-Mode Rootkit to Load TONESHELL Backdoor The Hacker Newsinfo@thehackernews.com (The Hacker News)

The Chinese hacking group known as Mustang Panda has leveraged a previously undocumented kernel-mode rootkit driver to deliver a new variant of backdoor dubbed TONESHELL in a cyber attack detected in mid-2025 targeting an unspecified entity in Asia. The findings come from Kaspersky, which observed the new backdoor variant in cyber espionage campaigns mounted by […]

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Feasible strategies in three-way conflict analysis with three-valued ratings AI updates on arXiv.org

Feasible strategies in three-way conflict analysis with three-valued ratingscs.AI updates on arXiv.org arXiv:2512.21420v2 Announce Type: new
Abstract: Most existing work on three-way conflict analysis has focused on trisecting agent pairs, agents, or issues, which contributes to understanding the nature of conflicts but falls short in addressing their resolution. Specifically, the formulation of feasible strategies, as an essential component of conflict resolution and mitigation, has received insufficient scholarly attention. Therefore, this paper aims to investigate feasible strategies from two perspectives of consistency and non-consistency. Particularly, we begin with computing the overall rating of a clique of agents based on positive and negative similarity degrees. Afterwards, considering the weights of both agents and issues, we propose weighted consistency and non-consistency measures, which are respectively used to identify the feasible strategies for a clique of agents. Algorithms are developed to identify feasible strategies, $L$-order feasible strategies, and the corresponding optimal ones. Finally, to demonstrate the practicality, effectiveness, and superiority of the proposed models, we apply them to two commonly used case studies on NBA labor negotiations and development plans for Gansu Province and conduct a sensitivity analysis on parameters and a comparative analysis with existing state-of-the-art conflict analysis approaches. The comparison results demonstrate that our conflict resolution models outperform the conventional approaches by unifying weighted agent-issue evaluation with consistency and non-consistency measures to enable the systematic identification of not only feasible strategies but also optimal solutions.

 arXiv:2512.21420v2 Announce Type: new
Abstract: Most existing work on three-way conflict analysis has focused on trisecting agent pairs, agents, or issues, which contributes to understanding the nature of conflicts but falls short in addressing their resolution. Specifically, the formulation of feasible strategies, as an essential component of conflict resolution and mitigation, has received insufficient scholarly attention. Therefore, this paper aims to investigate feasible strategies from two perspectives of consistency and non-consistency. Particularly, we begin with computing the overall rating of a clique of agents based on positive and negative similarity degrees. Afterwards, considering the weights of both agents and issues, we propose weighted consistency and non-consistency measures, which are respectively used to identify the feasible strategies for a clique of agents. Algorithms are developed to identify feasible strategies, $L$-order feasible strategies, and the corresponding optimal ones. Finally, to demonstrate the practicality, effectiveness, and superiority of the proposed models, we apply them to two commonly used case studies on NBA labor negotiations and development plans for Gansu Province and conduct a sensitivity analysis on parameters and a comparative analysis with existing state-of-the-art conflict analysis approaches. The comparison results demonstrate that our conflict resolution models outperform the conventional approaches by unifying weighted agent-issue evaluation with consistency and non-consistency measures to enable the systematic identification of not only feasible strategies but also optimal solutions. Read More