Knowledge catalogue
arXiv:2610.07692v1 Announce Type: new Abstract: Human video offers a scalable source of experience for dexterous robot learning, but obtaining motion and tactile supervision while preserving bare hand
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:2610.06862v1 Announce Type: new Abstract: **Context:** Deep Neural Networks (DNNs) increasingly control Cyber-Physical Systems (CPSs), yet small input perturbations can cause unsafe system-level
arXiv:2610.08534v1 Announce Type: new Abstract: Understanding the principles behind Shampoo has recently guided the development of more effective neural network optimizers. These methods learn a preco
arXiv:2610.08577v1 Announce Type: cross Abstract: While unlearning seeks to negate undesired capabilities acquired through learning, little research has examined how the way models learn shapes their
arXiv:2610.07900v1 Announce Type: cross Abstract: Wi-Fi 9 is expected to go beyond mere communication and provide new services such as sensing or computation. At this juncture, Artificial Intelligence
arXiv:2610.07551v1 Announce Type: cross Abstract: Learning Gaussian mixture models (GMMs) using the Expectation-Maximization (EM) algorithm and its gradient-based variants is a fundamental problem in
Google AI has published a new blog post titled “Learn more about identifying AI‑generated content,” announcing tools that make it easier to spot machine‑created text on a global scale. The article – r
arXiv:2610.07196v1 Announce Type: cross Abstract: Variational autoencoders are powerful representation learning models that map complex data into low-dimensional latent spaces, enabling the discovery
arXiv:2610.07638v1 Announce Type: new Abstract: As part of learning to play complex games, human players develop develop abstractions for concepts and strategies of gameplay consistent with game rules
arXiv:2610.08405v1 Announce Type: cross Abstract: Large Language Models have emerged as promising tools for software vulnerability analysis, but their effectiveness depends heavily on prompt design. E
arXiv:2509.26513v2 Announce Type: replace Abstract: Generating large and diverse obstacle datasets to learn motion planning in environments with dynamic obstacles is challenging due to the vast space
arXiv:2610.07184v1 Announce Type: cross Abstract: A key challenge in building AI systems for scientific research is enabling extit{scientific exploration}: the systematic process of investigating unkn
Looks like you copied Chandra OCR 2 into your repo, renamed it, changed the license, and made the output worse (your olmocr score is 83.8 vs our 85.8). Introducing interfaze-1-lite, the first general
arXiv:2610.06996v1 Announce Type: cross Abstract: Block diffusion language models keep a large key-value (KV) cache throughout generation and attend to it at every denoising step, limiting both memory
arXiv:2610.08214v1 Announce Type: new Abstract: We report on an approach to teaching logic to mixed groups of computer science, mathematics, and philosophy students, based on the logico-pluralistic Lo
arXiv:2610.08479v1 Announce Type: cross Abstract: Few-shot meta-learning traditionally formulates task adaptation either as analytical gradient descent through unrolled computational graphs or as metr
arXiv:2610.08131v1 Announce Type: cross Abstract: Achieving compositional concept generalization (CoCoGen), the ability to understand novel situations by recombining learned primitives, remains a fund
arXiv:2610.07800v1 Announce Type: cross Abstract: Artificial Intelligence (AI) tools are widely used to support decision making in tasks and domains where no immediate performance feedback is availabl
arXiv:2610.08735v1 Announce Type: new Abstract: In online inverse linear optimization, a learner recommends an action and then observes the choice of an expert who maximizes a fixed, unknown linear ob
arXiv:2610.08296v1 Announce Type: new Abstract: Generative models have the potential to accelerate inorganic materials discovery by enabling inverse design, but generating experimentally realisable cr
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
Enterprise RAG unlocks insights from knowledge sources like SharePoint, Google Drive, and Confluence, but those sources carry complex permissions. Learn how Amazon Quick and Amazon Bedrock Knowledge B
arXiv:2610.06955v1 Announce Type: cross Abstract: Humans inherently understand the physical world through an active process. When sensory evidence is insufficient to infer physical properties, we natu
arXiv:2610.08355v1 Announce Type: cross Abstract: Flow-matching models start from an isotropic Gaussian source, the standard choice when the correlation structure of the data is unknown in advance. Fo
arXiv:2610.07002v1 Announce Type: cross Abstract: Diffusion models learn semantic representations while generating images. In the Decoupled Diffusion Transformer (DDT), a condition encoder provides fe
arXiv:2610.07499v1 Announce Type: new Abstract: Multimodal wearable systems must remain reliable when sensor streams become noisy or unavailable. Existing multimodal test-time adaptation (TTA) methods
arXiv:2512.23441v2 Announce Type: replace-cross Abstract: Temporally aware image representations are crucial for capturing disease progression in 3D volumes of longitudinal medical datasets. However,
arXiv:2610.07038v1 Announce Type: new Abstract: Modern forecasting models are often updated after deployment so they can respond to changing data. These updates can also make predictions worse, so pra
The real news here isn’t the result; it’s what we were not told. 1. AI once tried to be a science. Now we get stuff like the completely vague report from OpenAI below, and a lot of ignorant questions
arXiv:2610.06962v1 Announce Type: cross Abstract: In many review workflows the verdict is the only thing retained. The passages behind it are not marked, because that annotation costs far more than re
arXiv:2610.07097v1 Announce Type: new Abstract: Experimental studies of generative AI in education mostly report average effects, yet field evidence shows that AI can narrow attainment gaps or widen t
We're sharing progress on ChatGPT for Teens, our ChatGPT experience for people under 18, alongside a preview of College Planner, new study tools, and support for college advisers and teen voices. Chat
I'm a Ai engineer with about 2 years work experience, but let's just assume that I was a undergraduate student just starting out where would I begin so that I can publish a A* conference paper at some
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:2610.04039v1 Announce Type: cross Abstract: Applications such as engineering design often require us to optimize a black-box function, i.e., a system whose inner processing is not analytically k
arXiv:2506.09368v2 Announce Type: replace Abstract: Anomaly detection (AD) plays a pivotal role across diverse domains, including cybersecurity, finance, healthcare, and industrial manufacturing, by i
arXiv:2610.06174v1 Announce Type: new Abstract: Can LLMs recognize degradation in their own computational substrate? Inspired by anosognosia, a neurological condition in which patients fail to recogni
arXiv:2610.04624v1 Announce Type: new Abstract: Recovering Partial Differential Equation (PDE) coefficient fields from extremely sparse observations is a severely ill-posed inverse problem for which g
arXiv:2610.05125v1 Announce Type: new Abstract: Masked Diffusion Language Models (MDLMs) generate sequences by iteratively replacing masked tokens with model predictions. At each denoising step, the d
Learn how to administer Amazon SageMaker HyperPod through Amazon SageMaker Unified Studio while preserving cluster governance. This post shows platform teams how to design infrastructure boundaries, g
arXiv:2103.16559v3 Announce Type: cross Abstract: Most successful self-supervised learning methods are trained to align the representations of two independent views from the data. State-of-the-art met
Off-the-shelf AI assistants forget you between conversations. This post shows how to build a personal assistant that accumulates context using OpenClaw on Amazon Bedrock AgentCore runtime, with AgentC
arXiv:2610.04553v1 Announce Type: cross Abstract: The long observational record of He I 10830 {AA} offers a means to investigate solar morphology before modern extreme-ultraviolet (EUV) imaging. We ad
arXiv:2610.04211v1 Announce Type: cross Abstract: Skeletal motion is stored as every joint's transform at every frame, yet most of it is implied by the body rather than by what the motion is about. Co
arXiv:2610.06331v1 Announce Type: new Abstract: Human demonstrations offer rich examples of precise dexterous manipulation and a promising source of robot training data. However, high-fidelity reprodu
arXiv:2610.05333v1 Announce Type: new Abstract: Generative foundation models are attracting interest for their ability to produce desired outputs from demonstrations given at inference time, without u
arXiv:2610.04933v1 Announce Type: cross Abstract: Scaling robot data and model capacity has improved Vision-Language-Action (VLA) policies, but further progress is constrained by the high cost of robo
arXiv:2610.03765v1 Announce Type: new Abstract: Discrete motion tokenizers encode motion as atomic units and are widely used for co-speech gesture generation. It remains unclear which motion propertie
arXiv:2610.05297v1 Announce Type: new Abstract: We ask whether a neural network can learn a structure-preserving map from a compressed latent space to a Hilbert-space representation. Using an 8-dimens
arXiv:2610.04044v1 Announce Type: new Abstract: The quadratic attention cost of Vision Transformers (ViTs) forces a trade-off between spatial resolution and rollout horizon, particularly for fine-scal
arXiv:2610.05397v1 Announce Type: new Abstract: Generative modeling of graph-structured data is crucial for tasks ranging from drug discovery to social network simulation. Among these models, denoisin
I've been working on a font searching tool for about a year now, and my investigations have centered around pre-training neural networks to produce embeddings of each font. I usually then need to post
arXiv:2610.06221v1 Announce Type: new Abstract: Pretrained diffusion models provide powerful image priors for training-free posterior sampling in image restoration. To guide this sampling process, fre
arXiv:2610.05711v1 Announce Type: cross Abstract: Strong image generation models are conditioned on class labels, aligned to frozen pretrained encoders, or built on separately trained autoencoders. Wh
arXiv:2509.24117v2 Announce Type: replace Abstract: Inverse problems governed by partial differential equations (PDEs) arise widely in science and engineering, but are often ill-posed and limited by s
arXiv:2610.05834v1 Announce Type: new Abstract: Broad Learning System (BLS) supports analytical training and incremental expansion, but its growth needs guidance on which inputs new blocks should lear
arXiv:2610.06677v1 Announce Type: new Abstract: Mixture-of-experts (MoE) routers typically apply softmax to the router scores and keep the top-K experts, making every token use exactly K experts. Spar
arXiv:2610.06784v1 Announce Type: cross Abstract: Much of the recent progress in machine learning domains such as language models has come from scaling laws that predict performance as a function of t
arXiv:2510.04455v3 Announce Type: replace-cross Abstract: Data-driven inverse optimization for mixed-integer linear programs (MILPs), which seeks to learn an objective function and constraints consist