Search: “applications”

arXiv:2606.01948v1 Announce Type: cross Abstract: The growing popularity of group activities has increased the need for methods that provide recommendations to groups of users given their individual p

arXiv:2606.01172v1 Announce Type: new Abstract: Modeling unknown latent functions from finite, irregularly sampled measurements is a recurring challenge across science and engineering. Neural processe

arXiv:2606.00981v1 Announce Type: new Abstract: LLMs can plan by either generating action sequences directly as a Planner or translating tasks into domain specific language for an external solver as a

arXiv:2606.00808v1 Announce Type: new Abstract: Source-free graph domain adaptation (SF-GDA) aims to adapt source-trained graph models to unlabeled target graphs when source graphs are no longer acces

arXiv:2606.01939v1 Announce Type: new Abstract: Precise 3D representations of industrial environments enable tasks such as robot localization and digital twin generation. We propose SAVMap, a method f

arXiv:2602.23234v4 Announce Type: replace-cross Abstract: Large-scale commercial search systems optimize for relevance to drive successful sessions that help users find what they are looking for. To m

arXiv:2512.09065v2 Announce Type: replace-cross Abstract: Many indoor workspaces are quasi-static: their global geometric layout is stable, but local semantics change continually, producing repetitive

arXiv:2606.01723v1 Announce Type: cross Abstract: Real-world regression often exhibits shortcuts: attributes that are spuriously correlated with continuous targets in training, yet unreliable under de

Since a lot of comments ask about it, they cannot really say anything about code quality using their methods. In part, the reason humans are the bottleneck is because humans are doing some sort of qua

arXiv:2606.00509v1 Announce Type: new Abstract: Recovering surface normals from single view polarization images in complex media remains challenging. This paper focuses on ice as a representative comp

The everything apps still look a lot like hybrids between chatbots and IDEs, rather than something built for general knowledge work. Too much assuming linearity & that final outputs are the only goal,

The execution across Elon Musk’s companies right now is operating at an unprecedented scale • SpaceX — The largest IPO in history expected around June 12 • xAI — Grok V9 (1.5T parameters) launching mi

The Economist: The IPOs of SpaceX, Anthropic, and OpenAI could add up to 4T to US stock market value within months, fueling concerns they could trigger more capital-raising — They promise to be the bi

arXiv:2606.01670v1 Announce Type: cross Abstract: Recently, Generative Recommenders (GRs) have emerged as a transformative recommendation paradigm by replacing traditional item IDs with semantic indic

arXiv:2606.00040v1 Announce Type: cross Abstract: As Generative AI (GenAI) becomes integral to education, fostering GenAI literacy is critical. However, current assessments largely rely on self-report

arXiv:2606.01737v1 Announce Type: new Abstract: Traffic accident liability analysis is a critical yet challenging task in intelligent transportation and legal assistance. Existing methods often suffer

arXiv:2606.01777v1 Announce Type: new Abstract: Transparent objects remain challenging for robotic perception due to unreliable depth sensing caused by refraction and reflection. While prior approache

arXiv:2606.01046v1 Announce Type: new Abstract: The development of Large Language Models (LLMs) has significantly improved travel planning applications, yet evaluating such models is limited by existi

arXiv:2606.00979v1 Announce Type: new Abstract: Accurate Estimated Time of Arrival (ETA) prediction on checkout page is crucial in instant logistics for enhancing user satisfaction, optimizing dispatc

arXiv:2512.14364v3 Announce Type: replace Abstract: Holistic 3D scene understanding involves capturing and parsing unstructured 3D environments. Due to the inherent complexity of the real world, exist

arXiv:2606.00422v1 Announce Type: cross Abstract: Modern recommendation systems predominantly train retrieval and ranking as separate models despite both increasingly relying on large transformers enc

arXiv:2606.01955v1 Announce Type: cross Abstract: WALL-WM is a World Action Model that shifts video-action learning from chunk-centric optimization to event-grounded Vision-Language-Action pretraining

We’re making Codex more useful for your work by expanding plugins beyond individual tools. These plugins turn Codex into a specialist for a specific role with a single install, no coding required. Cod

arXiv:2606.01999v1 Announce Type: cross Abstract: Modern deep learning models for forecasting groups of time series rely on increasingly longer observation windows. However, the benefit of increasing

Financial institutions have spent years building AI: fraud models, credit models, recommendation engines and risk systems. While this sprawl of task-specific models has been effective, it’s also const

arXiv:2602.12819v2 Announce Type: replace-cross Abstract: In this paper, we present WISE, an open-source audiovisual search engine which integrates a range of multimodal retrieval capabilities into a

arXiv:2605.30399v1 Announce Type: cross Abstract: The aquaculture industry needs to address several challenges to secure sustainable seafood production that can serve an increasing global demand. One

arXiv:2605.30578v1 Announce Type: cross Abstract: Adversarial patches are physical patterns attached to real objects to mislead AI vision systems. Their real-world risk is not determined by a single s

arXiv:2605.31272v1 Announce Type: new Abstract: As predictive models are increasingly deployed in high-stakes settings such as credit approval, there is a growing need for post-hoc methods that provid

The Bot Company, a 2 billion San Francisco startup founded by Tesla and Cruise alumni, rented residential properties through Airbnb under false pretenses to conduct prototype testing on household robo

arXiv:2605.31016v1 Announce Type: new Abstract: Graph condensation (GC) is pivotal for enabling Graph Neural Networks (GNNs) deployment in resource-constrained scenarios by compressing large-scale gra

arXiv:2605.31437v1 Announce Type: new Abstract: CT interpretation requires radiologists to review hundreds of volumetric slices per examination, making reporting time-consuming and highly expertise-de

arXiv:2605.05520v2 Announce Type: replace Abstract: Commercial Microwave Links (CMLs) offer dense spatial coverage for rainfall sensing but produce path-integrated measurements that make accurate grou

arXiv:2605.30987v1 Announce Type: new Abstract: The tasks of object removal and inpainting 3D Gaussian Splatting (3DGS) scenes face challenges such as 3D consistency across camera views. In comparing

arXiv:2501.04661v3 Announce Type: replace-cross Abstract: The web-scale of pretraining data has created an important evaluation challenge: to disentangle linguistic competence on cases well-represente

arXiv:2605.31338v1 Announce Type: new Abstract: Statutory references are central to legal language understanding, but are difficult to process automatically, as they appear in compact and variable sur

arXiv:2605.30981v1 Announce Type: new Abstract: Autoregressive language models frequently degrade during long-horizon generation, producing repetitive text, losing instruction adherence, and exhibitin

arXiv:2605.31093v1 Announce Type: new Abstract: Breast cancer is a major global health concern, and mammography screening plays a central role in early detection. The large volume of screening examina

arXiv:2605.31164v1 Announce Type: cross Abstract: Training data plays a central role in large language models (LLMs) optimization, motivating extensive research on data scheduling strategies. Most exi

arXiv:2605.30642v1 Announce Type: new Abstract: Generative models have a persistent limitation: their tendency to memorize training data can create legal liabilities and erode creative diversity. Unde

arXiv:2605.30456v1 Announce Type: new Abstract: Many learning tasks in science and engineering are characterized by sparse datasets, which limits the effectiveness of purely data-driven approaches. At

arXiv:2605.30934v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit systematic differences in moral reasoning across languages, yet the source of this variation remains unclear. We

arXiv:2605.31487v1 Announce Type: new Abstract: Deploying computer vision models in Warehouse Facilities traditionally requires extensive resources for camera mounting, image collection, annotation, t

arXiv:2602.02680v2 Announce Type: replace Abstract: The growing scale of deep neural networks, encompassing large language models (LLMs) and vision transformers (ViTs), has made training from scratch

For those who wants stats, rather than anecdotes https://x.com/emollick/status/1983217724714066310?s=20 👀New data on the corporate ROI from generative AI from a large-scale tracking survey by my colle

arXiv:2605.31193v1 Announce Type: new Abstract: Real-world multimodal systems must be robust against low-quality data, such as sensor noise, incomplete multimodal data and conflicting inputs. However,