Learning Ecosystems
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Design Once, Deploy at Scale: Template-Driven ML Development for Large Model Ecosystems
arXiv:2603.24963v3 Announce Type: replace Abstract: Modern computational advertising platforms typically rely on recommendation systems to predict user responses, such as click-through rates, conversion rates, and other optimization events. To support a wide variety of product surfaces and advertiser goals, these platforms frequently maintain an extensive ecosystem of machine learning (ML) models. However, operating at this scale creates significant development and efficiency challenges.
Learning to Evaluate: Cost-Effective Model Evaluation on Unlabeled Data with Meta-Learning
Announce Type: replace Abstract: The rapid advancement of machine learning has led to an unprecedented expansion of model ecosystems, making it increasingly difficult to assess the reliability of newly released models on unseen and unlabeled data. Existing evaluation pipelines typically rely on costly annotation, repeated fine-tuning, or assumptions that do not generalize well to new models. We introduce MetaEvaluator, a cost-effective, model-agnostic framework for fast, label-free...
Learning to Evaluate: Cost-Effective Model Evaluation on Unlabeled Data with Meta-Learning
Announce Type: replace Abstract: The rapid advancement of machine learning has led to an unprecedented expansion of model ecosystems, making it increasingly difficult to assess the reliability of newly released models on unseen and unlabeled data. Existing evaluation pipelines typically rely on costly annotation, repeated fine-tuning, or assumptions that do not generalize well to new models. We introduce MetaEvaluator, a cost-effective, model-agnostic framework for fast, label-free...
Powering An Ecosystem Of Pedagogical AI Agents: A Validation Strategy For A Unified Data Architecture
Announce Type: new Abstract: The application of AI in education has evolved from monolithic intelligent tutoring systems to a diverse ecosystem of pedagogical agents, including conversational assistants, virtual coaches, and adaptive tutors. This shift requires a unified and scalable data architecture to manage the complex information feedback loops between human instructors, learners, and the varied AI agents. The design, development, and deployment of the data architecture in turn raises a...
Stupid hot: Heat waves cause cognitive changes in animals, making them more aggressive and unable to complete basic tasks
Stupid hot: Heat waves cause cognitive changes in animals, making them more aggressive and unable to complete basic tasks As temperatures rise, some creatures pick fights while others struggle to learn. The consequences of these behavioral changes may ripple through ecosystems. On a blazing hot day in South Africa, female southern pied babblers can't think straight.
MineXplore: An Open-Source Reinforcement Learning Exploration Benchmark for GNSS-Denied Underground Environment
Announce Type: new Abstract: Underground mines present extreme conditions for autonomous robot navigation: GPS is denied, lighting is degraded, and tunnel topology is loop-rich and non-convex. Simulation benchmarks grounded in real production-mine geometry and compatible with GPU-accelerated learning pipelines do not yet exist in the open-source ecosystem. We present MineXplore, an open-source MuJoCo-based navigation benchmark derived from the Leung et al. 2017
The Fundamental Limits of Fraud Detection in Card Payment Networks
Announce Type: replace Abstract: Card payment fraud detection is usually framed as a supervised classification problem. Although this approach has generated practical progress, improvement has remained incremental despite major advances in model architecture. We argue that this is not mainly a failure of function approximation or optimization, but a consequence of structural information impairments inherent to the payment ecosystem.
Blockchain Infrastructure for Intelligent Cyber--Physical--Social Systems:Post-Quantum Security, Interoperability, and Trustworthy Data Economies in the Era of Embodied AI
Announce Type: new Abstract: The deployment of embodied artificial intelligence via world-model-based robotics presents a transformative opportunity for blockchain infrastructure, establishing urgent demand for trustworthy data provenance, cross-organizational governance, and incentive-compatible sharing across decentralized ecosystems. Simultaneously, quantum computing advances recognized by the 2025 Nobel Prize in Physics and the Turing Award threaten the cryptographic primitives securing...
EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale
arXiv:2604.17406v3 Announce Type: replace Abstract: The convergence of large language models and agents is catalyzing a new era of scientific discovery: Agentic Science. While the scientific method is inherently iterative, existing agent frameworks are predominantly static, narrowly scoped, and lack the capacity to learn from trial and error. To bridge this gap, we present EvoMaster, a foundational evolving agent framework engineered specifically for Agentic Science at Scale.
Taiwan's Lai: Status quo is key to secure tech supply chains
Taiwan's Lai: Status quo is key to secure tech supply chains June 2, 2026Taiwanese President Lai Ching-te opened the COMPUTEX technology trade fair in Taipei on Tuesday, saying that maintaining the political status quo is the most responsible approach the island can take to secure global supply chains. As the home for the world's largest contract chipmaker, TSMC, Taiwan is a key equipment supplier for companies including Nvidia and Apple. But its political status is a constant source of...