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
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
CISA ordered U.S. federal agencies to patch an actively exploited MongoDB vulnerability (MongoBleed) that can be exploited to steal credentials, API keys, and other sensitive data. […] Read More
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 […]
The European Space Agency (ESA) confirmed that attackers recently breached servers outside its corporate network, which contained what it described as “unclassified” information on collaborative engineering activities. […] Read More
A new cybercrime tool called ErrTraffic allows threat actors to automate ClickFix attacks by generating ‘fake glitches’ on compromised websites to lure users into downloading payloads or following malicious instructions […] Read More
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 […]
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
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 […]
DynaMix: Generalizable Person Re-identification via Dynamic Relabeling and Mixed Data Samplingcs.AI updates on arXiv.org arXiv:2511.19067v2 Announce Type: replace-cross
Abstract: Generalizable person re-identification (Re-ID) aims to recognize individuals across unseen cameras and environments. While existing methods rely heavily on limited labeled multi-camera data, we propose DynaMix, a novel method that effectively combines manually labeled multi-camera and large-scale pseudo-labeled single-camera data. Unlike prior works, DynaMix dynamically adapts to the structure and noise of the training data through three core components: (1) a Relabeling Module that refines pseudo-labels of single-camera identities on-the-fly; (2) an Efficient Centroids Module that maintains robust identity representations under a large identity space; and (3) a Data Sampling Module that carefully composes mixed data mini-batches to balance learning complexity and intra-batch diversity. All components are specifically designed to operate efficiently at scale, enabling effective training on millions of images and hundreds of thousands of identities. Extensive experiments demonstrate that DynaMix consistently outperforms state-of-the-art methods in generalizable person Re-ID.
arXiv:2511.19067v2 Announce Type: replace-cross
Abstract: Generalizable person re-identification (Re-ID) aims to recognize individuals across unseen cameras and environments. While existing methods rely heavily on limited labeled multi-camera data, we propose DynaMix, a novel method that effectively combines manually labeled multi-camera and large-scale pseudo-labeled single-camera data. Unlike prior works, DynaMix dynamically adapts to the structure and noise of the training data through three core components: (1) a Relabeling Module that refines pseudo-labels of single-camera identities on-the-fly; (2) an Efficient Centroids Module that maintains robust identity representations under a large identity space; and (3) a Data Sampling Module that carefully composes mixed data mini-batches to balance learning complexity and intra-batch diversity. All components are specifically designed to operate efficiently at scale, enabling effective training on millions of images and hundreds of thousands of identities. Extensive experiments demonstrate that DynaMix consistently outperforms state-of-the-art methods in generalizable person Re-ID. Read More