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arXiv:2605.09046v1 Announce Type: new Abstract: In many real-world robotic tasks, robots must generate dynamically feasible motions that reliably reach desired goals even under uncertainty. Yet existi

arXiv:2601.02366v2 Announce Type: replace-cross Abstract: Graph-based recommendation has achieved great success in recent years. The classical graph recommendation model utilizes ID embedding to store

arXiv:2605.10687v1 Announce Type: new Abstract: Turbulent dynamical systems are characterized by nonlinear interactions and stochastic effects that generate coupled statistical quantities, such as non

The new Cofounder site is literally a step-by-step guide on how to start a company. When i started my first company there was all sorts of stuff i had to learn and all of the guides were SEO maxxed sl

arXiv:2605.10019v1 Announce Type: cross Abstract: Generative models trained on finite data face a fundamental tension: their score-matching or next-token objective converges to the empirical training

arXiv:2605.10373v1 Announce Type: cross Abstract: Large language models have significantly improved natural language interfaces to databases by translating user questions into executable queries. In p

arXiv:2605.10640v1 Announce Type: cross Abstract: Continual Pre-Training (CPT) is essential for enabling Language Models (LMs) to integrate new knowledge without erasing old. While classical CPT techn

arXiv:2605.10567v1 Announce Type: new Abstract: In this paper, we aim to jointly model the geometry, appearance, and physical information of 3D scenes solely from dynamic multi-view videos, without re

arXiv:2605.09908v1 Announce Type: cross Abstract: Current approaches to detecting depression and anxiety from speech primarily rely on machine learning techniques that utilize hand-engineered paraling

arXiv:2605.09461v1 Announce Type: new Abstract: Automated vulnerability detection is a fundamental task in software security, yet existing learning-based methods still struggle to capture the structur

OpenAI confirmed to Ethan Mollick that Study Mode remains active and can be accessed through the /study and /learn shortcuts, though this feature may not be widely known among general users. The acces

arXiv:2605.08298v1 Announce Type: cross Abstract: Reusing the early layers of cohort-trained INRs as initialization for new signals has been shown to accelerate and improve signal fitting, yet it rema

arXiv:2411.18111v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) that incorporate visual models and large language models have achieved impressive results across cross-modal un

arXiv:2605.10242v1 Announce Type: cross Abstract: Unsupervised tabular anomaly detection methods typically learn feature patterns from normal samples during training and subsequently identify samples

arXiv:2604.02564v2 Announce Type: replace-cross Abstract: We present MaskGen, a theoretically grounded and deliberately simple approach for domain generalization in 3D biomedical image segmentation. M

World models recently made our list of 10 Things That Matter in AI Right Now. Watch executive editor Niall Firth explain why this emerging area of AI is gaining so much attention. Join MIT Technology

arXiv:2605.09789v1 Announce Type: new Abstract: Dexterous manipulation is physics-intensive and highly sensitive to modeling errors and perception noise, making sim-to-real transfer prohibitively chal

arXiv:2310.15288v3 Announce Type: replace Abstract: Reward learning techniques enable machine learning systems to learn objectives from human feedback. A core limitation of these systems is their assu

Amazon Quick helps turn your large enterprise data into fast and accurate AI-powered decisions. In this post, you will learn about five new capabilities of Amazon Quick that accelerate how data profes

arXiv:2511.09016v2 Announce Type: replace-cross Abstract: The Kalman filter and Rauch-Tung-Striebel (RTS) smoother are optimal for state estimation in linear dynamic systems. With nonlinear systems, t

arXiv:2605.07034v1 Announce Type: cross Abstract: Modern cybersecurity relies heavily on static machine-learning-based malware classifiers. However, transformations such as packing and other non-seman

arXiv:2605.07277v1 Announce Type: cross Abstract: Many scientific and combinatorial problems admit multiple correct solutions, not a single label. Standard supervised learning resolves this ambiguity

arXiv:2605.06969v1 Announce Type: new Abstract: Infrared-Visible image fusion (IVIF) aims to integrate thermal information and detailed spatial structures into a single fused image to enhance percepti

In this post, you will learn how to set up the Exa integration in Strands Agents, understand the two core tools it exposes, and walk through real-world use cases that show how agents use web search to

arXiv:2605.07886v1 Announce Type: cross Abstract: Online learning from a stream of data is a defining feature of intelligence, yet modern machine learning systems often struggle in this setting, espec

arXiv:2605.07119v1 Announce Type: cross Abstract: Classical clustering methods usually return either a finite partition of the observed data or a finite dendrogram over it. This finite-sample view is

arXiv:2605.08077v1 Announce Type: new Abstract: Knowledge Graph Question Answering (KGQA) has shown promise for grounded and interpretable reasoning, yet existing approaches often fail to provide reli

Cursor is an AI-powered code editor that analyzes entire conversation threads to understand context before generating solutions and automatically creating pull requests for team review. This feature s

arXiv:2605.07940v1 Announce Type: new Abstract: Exemplar-based image editing applies a transformation defined by a source-target image pair to a new query image. Existing methods rely on a pair-of-pai

Sarah Perez / TechCrunch: Digg relaunches as an aggregator of AI news and social media commentary, with plans to expand to other topics; its previous reboot shut down in March — Digg is back from the

Cursor AI has rolled out effort levels functionality to all users on usage-based Bugbot plans, allowing users to configure these settings directly through their Bugbot dashboard. This feature enables

arXiv:2605.08073v1 Announce Type: cross Abstract: Recent event-based image reconstruction methods predominantly rely on Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) to process c

arXiv:2605.07097v1 Announce Type: cross Abstract: We show that, in a precise sense, a broad class of feedforward neural networks learn (have finite sample complexity) in the PAC model: every fixed fin

Explore the beginner's guide to ComfyHub. ComfyHub is the public home for community-built workflows and apps — the fastest way to find and run what the ComfyUI ecosystem has already created, without n

arXiv:2510.01510v3 Announce Type: replace Abstract: We study the problem of zero-shot link prediction on knowledge graphs (KGs), which requires models to generalize to novel entities and novel relatio

arXiv:2605.07474v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models hold great promise for general-purpose robotic intelligence, yet scaling up such models is severely bottlenecked b

arXiv:2605.07203v1 Announce Type: new Abstract: Scene change detection methods built on Gaussian splatting universally follow a render-then-compare paradigm: the pre-change scene is rendered into 2D a

arXiv:2605.07933v1 Announce Type: new Abstract: Latent diffusion models offer an attractive alternative to discrete diffusion for non-autoregressive text generation by operating on continuous text rep

arXiv:2508.05803v2 Announce Type: replace Abstract: Human memory is fleeting. As words are processed, the exact wordforms that make up incoming sentences are rapidly lost. Cognitive scientists have lo

arXiv:2506.12362v3 Announce Type: replace-cross Abstract: Inductive link prediction with knowledge hypergraphs is the task of predicting missing hyperedges involving completely novel entities (i.e., n

I'm delighted that @coursera and @udemy have come together as one company to serve learners. Both Coursera and Udemy were founded with the belief that access to high-quality education changes lives. O

arXiv:2605.07491v1 Announce Type: new Abstract: This paper proposes a novel framework for implicit multi-camera system calibration utilizing Gaussian Process (GP) regression. Conventional explicit cal

arXiv:2605.07010v1 Announce Type: new Abstract: Identifying vulnerable transmission lines in power grids before a cascading failure occurs is challenging: existing methods can learn inter-line failure

arXiv:2605.07648v1 Announce Type: new Abstract: Learning parity functions, more general modular addition, is a challenging machine learning task due to its input sensitivity. A recent study substantia

arXiv:2310.02243v2 Announce Type: replace-cross Abstract: We study the problem of learning a local quantum Hamiltonian H given copies of its Gibbs state rho = e^{-eta H}/extrm{tr}(e^{-eta H}) at a kno

arXiv:2605.06676v1 Announce Type: cross Abstract: Long-context inference in Large Language Models (LLMs) is bottlenecked by the linear growth of Key-Value (KV) cache memory. Existing KV cache compress