Knowledge catalogue
arXiv:2610.10600v1 Announce Type: cross Abstract: Steinke and Zakynthinou(2020) introduces the Conditional Mutual Information (CMI) framework of analyzing the information complexity of learning algori
arXiv:2610.09518v1 Announce Type: new Abstract: As robots increasingly assist humans with diverse tasks, they need both geometric and semantic understanding of their surroundings. Moreover, robots oft
arXiv:2610.09661v1 Announce Type: new Abstract: Automatic Short Answer Scoring (ASAS) is central to NLP for Education. However, openly available benchmarks remain scarce, and existing datasets largely
arXiv:2610.09525v1 Announce Type: new Abstract: We introduce a calibration-first framework that produces supervision scores without access to ground-truth labels or a shared annotation space. Our fram
arXiv:2610.10198v1 Announce Type: new Abstract: Behavior Foundation Models (BFMs) are emerging as a paradigm for translating human intentions into executable humanoid behaviors. As these models evolve
arXiv:2610.10383v1 Announce Type: new Abstract: Boosting converts weak hypotheses with a small edge over random guessing into highly accurate predictors, but the expressive power of the resulting clas
arXiv:2610.09552v1 Announce Type: cross Abstract: Watermarking enables language model providers to identify text generated by their models. However, its desired properties can conflict (ie~stronger wa
arXiv:2610.09375v1 Announce Type: new Abstract: Organizations increasingly use frontier language models to analyze customer feedback, but answer quality also depends on how that feedback is organized
arXiv:2610.09285v1 Announce Type: cross Abstract: Many applications of physical AI run within finite or closed physical worlds with a limited set of physical laws governing object behavior. Examples i
arXiv:2610.10405v1 Announce Type: cross Abstract: Monitoring the chain-of-thought of reasoning artificial intelligence (AI) models remains a key approach to detecting deception and other forms of misb
arXiv:2605.06295v2 Announce Type: replace Abstract: How can an arbitrary attribution method be generalized from first principles to capture interactions? We answer this with the metagame, a conceptual
arXiv:2610.09087v1 Announce Type: new Abstract: Large language models are informing decisions with ever-higher stakes. As the consequences of their errors grow, a central question becomes harder to ig
arXiv:2610.09731v1 Announce Type: cross Abstract: Kernel methods are among the most powerful tools in machine learning and statistics, with a large number of successful applications. Their immense suc
arXiv:2610.07339v1 Announce Type: cross Abstract: Tactical Combat Casualty Care (TC3) requires responders to connect visual observations of injuries and interventions with established clinical guidanc
arXiv:2610.07271v1 Announce Type: new Abstract: Linkage algorithms for hierarchical clustering (HC) are a powerful and efficient framework for constructing clustering trees, yet it is often unclear wh
arXiv:2610.08210v1 Announce Type: cross Abstract: For a given data distribution (X_t)_{t in N} sim Q i.i.d., we investigate the hypothesis testing problem: H_0: Q = P_0 vs. H_1: Q = P_1, for two diffe
arXiv:2610.08069v1 Announce Type: new Abstract: A mean shift between two data sources can be easy to detect but hard to remove without substantially changing their representations. We cast its removal
On October 7, 2026 OpenAI released a session titled “Explore ideas through interactive visuals that respond as you learn, try, and discover.” The webcast showcased real‑time visual tools that adapt to
arXiv:2610.07258v1 Announce Type: cross Abstract: Enterprise AI agents that share a memory store face two unaddressed risks: sensitive data can leak through legitimately computed results the requester
arXiv:2610.08337v1 Announce Type: cross Abstract: Public redispatch records provide empirical data for grid congestion forecasting, but delayed reporting, zero-inflated distributions, and temporal shi
arXiv:2610.08528v1 Announce Type: cross Abstract: Clinical diagnosis is inherently a structured reasoning process, yet existing deep learning models often bypass this structure by mapping image featur
arXiv:2610.08075v1 Announce Type: cross Abstract: Conditional neural fields represent signals continuously, but their effectiveness depends on how the conditional latent representations are inferred f
arXiv:2510.14878v3 Announce Type: replace-cross Abstract: We study kernel regression with common rotation-invariant kernels on real datasets including CIFAR-5m, SVHN, and ImageNet. We give a theoretic
arXiv:2610.08093v1 Announce Type: cross Abstract: Developing reliable models for clinical tasks, such as Medical Question Answering (QA), is severely constrained by the limited availability of high-qu
arXiv:2610.07650v1 Announce Type: new Abstract: Reusing a capability across heterogeneous robots still requires substantial human adaptation and verification: transferring a skill often means re-engin
arXiv:2610.08126v1 Announce Type: cross Abstract: Product Identification has sprung up to become one of the most challenging problems in the automation of the retail industry. With the new industry 5.
arXiv:2607.09985v2 Announce Type: replace Abstract: Object pose estimation is a fundamental problem in 3D vision. Although recent state-of-the-art approaches achieve strong performance, generalization
arXiv:2610.05518v1 Announce Type: cross Abstract: The Frechet distance is a de facto standard for evaluating generative models across domains, appearing as FID for images and FVD for videos. It summar
arXiv:2610.07384v1 Announce Type: cross Abstract: Individual animal re-identification from camera-trap imagery is an instance retrieval problem central to non-invasive wildlife monitoring: a query ima
arXiv:2610.06427v1 Announce Type: new Abstract: As robotic teams tackle increasingly complex tasks in dynamic and unstructured environments, effective coordination requires agents to maintain accurate
arXiv:2610.05367v1 Announce Type: cross Abstract: Proof auto-formalization translates natural-language (NL) theorems and proofs into a formal language (FL) such as Lean, enabling mechanical verificati
arXiv:2610.04444v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate, complete, and transform information in settings where their outputs can shape conseque
arXiv:2610.05863v1 Announce Type: new Abstract: High-quality child care in early life is a critical determinant of children's growth and development. Research on child care quality has been constraine
arXiv:2603.19621v2 Announce Type: replace Abstract: Deep Reinforcement Learning (DRL) provides a general-purpose methodology for training inventory policies that can leverage big data and compute. How
arXiv:2610.06250v1 Announce Type: new Abstract: World models, which learn how environments respond to actions, are emerging as a powerful paradigm for planning through imagined futures, transforming d
arXiv:2610.06844v1 Announce Type: new Abstract: Multimodal Diffusion Transformers (MM-DiTs) jointly process visual and textual representations throughout generation. These models repeatedly update the
arXiv:2610.06252v1 Announce Type: new Abstract: The Lipschitz property of a deep neural network provides a direct measure of its sensitivity to input perturbations and, when explicitly controlled, off
arXiv:2610.03898v1 Announce Type: new Abstract: Model-based control of an aquatic robotic platform depends on a hydrodynamic model that is costly to identify and specific to the hull, payload, and con
arXiv:2610.04038v1 Announce Type: new Abstract: Synthetic data are increasingly used as an alternative to sharing sensitive records. However, synthetic data generation does not guarantee privacy, as d
arXiv:2610.05352v1 Announce Type: new Abstract: Tabular foundation models (TFMs) outperform established machine learning models on tabular benchmarks through in-context learning. Building on this succ
arXiv:2610.05961v1 Announce Type: new Abstract: Valuing player actions in football requires accounting for strategic interactions among 22 players, including off-ball movements and defensive positioni
arXiv:2610.03773v1 Announce Type: cross Abstract: Soft tactile sensors elevate robotic touch through enhanced flexibility and adaptability, yet most existing designs depend on embedded electronics tha
arXiv:2610.03413v1 Announce Type: new Abstract: Sequential learning systems often make decisions from accumulated experience while receiving high-dimensional inputs whose distribution may change over
arXiv:2610.02661v1 Announce Type: new Abstract: Real-time data streams in Web of Things (WoT) and edge computing environments often evolve through latent regime changes. For online representation lear
arXiv:2610.02753v1 Announce Type: cross Abstract: The practical success of conditional image generation hinges on fine-grained differences in condition alignment and visual fidelity. Classifier-free g
arXiv:2610.03698v1 Announce Type: new Abstract: Self-supervised Vision Transformers (ViTs), such as DINOv2, learn rich visual representations, but the functions of their internal tokens remain poorly
arXiv:2610.02762v1 Announce Type: new Abstract: Dynamic LLM routers promise to cut inference costs by sending each query to the cheapest model that can answer it correctly. We analyze six commercial r
arXiv:2610.02557v1 Announce Type: new Abstract: As powerful AI systems reach and sometimes surpass the abilities of human experts across a range of cognitively demanding tasks, the problem of accurate
Hey all, I don't know if you guys are experiencing the same thing, but there is this behaviour that i have been noticing on the latest models on openAI (since sol 5.6) and Anthropic since Fable 5.1 an
arXiv:2610.03695v1 Announce Type: new Abstract: Modern chess engines are silent experts: they play at a superhuman level, but do not offer explanations for their play. On the other hand, language mode
Designed artifacts are ontological, shaping, and at times limiting, what becomes possible or imaginable. One path toward mitigating such foreclosures is giving people power over how systems are design
arXiv:2610.03650v1 Announce Type: cross Abstract: Federated Learning (FL) is a privacy-oriented learning paradigm that enables collaborative model training while keeping training data local to partici
arXiv:2610.02511v1 Announce Type: new Abstract: Advancements in high-resolution numerical weather prediction (NWP) and data assimilation (DA) have shaped the developments in deep learning (DL) archite
arXiv:2610.03512v1 Announce Type: new Abstract: Humans draw progressively: a few strokes, a look at the result, a stroke erased, a prompt revised. Image generators do not work this way. They typically
arXiv:2610.02615v1 Announce Type: new Abstract: Learning research, as one of its central goals, tries to measure, model, and understand how learning-problem properties affect average-case learning per
Again, Elon was already thinking seriously about Super Intelligence more than a decade before today’s SI boom Nick Bostrom’s 2014 book “Superintelligence” specifically thanks Elon Musk in its acknowle
Automated lint: 19 errors, 64915 warnings, 3 info
I’m more used to not interacting with AI so much, and when I do it’s usually Claude who is polite but acts more like a coworker or professor, it’s critical of my ideas and functions more helpfully. Re
arXiv:2610.00870v1 Announce Type: new Abstract: We present an educator-guided LLM pedagogical agent for scaffolded feedback in conceptual database design. Integrated into an entity--relationship diagr
arXiv:2610.01326v1 Announce Type: new Abstract: This paper presents the European Crisis Management Ontology (ECMO), a modular OWL-based ontology intended as a cross-sectoral reference for disaster ris