applications

arXiv:2602.01419v2 Announce Type: replace-cross Abstract: High-level Computer-Aided Process Planning (CAPP) generates manufacturing process plans from part specifications. It suffers from limited data

arXiv:2608.29315v1 Announce Type: cross Abstract: This work introduces Semantically-Guided Exploration (SGE), a modular exploration framework for ground vehicles that integrates pixel-level semantic s

arXiv:2608.28600v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance on mathematical reasoning benchmarks, yet the mathematically meaningful skills underlying their

arXiv:2608.29432v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models reduce inference cost by executing multiple actions per call, but longer horizons often degrade accuracy because raw

Anna Tong / Forbes: Sources: AfterQuery, which sells coding and finance training data to AI labs, has hit a valuation of 3.2B, up from 300M in April, and is profitable — Twenty three year-old Spencer

arXiv:2608.29360v1 Announce Type: new Abstract: Spatiotemporal graphs underpin applications such as traffic forecasting, weather forecasting, and healthcare monitoring. Privacy regulations such as the

arXiv:2608.29145v1 Announce Type: cross Abstract: The rapid expansion of low Earth orbit satellites such as Starlink is increasingly contaminating astronomical surveys. In practice, contaminated image

arXiv:2608.28702v1 Announce Type: new Abstract: Deformable 3D Gaussian Splatting (D-3DGS) reconstructs dynamic scenes by deforming a canonical set of 3D Gaussians through a deformation field of frame

The big change in the past year is that for general individual use (including individual use inside firms) OpenAI & Anthropic have run away with the game. They keep trading leads; you can pick either

arXiv:2608.30224v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to annotate structured product data in e-commerce, but early deployment often begins as a cold-star

arXiv:2511.21799v2 Announce Type: replace Abstract: Real-world machine learning (ML) pipelines rarely produce a single model; instead, they produce a Rashomon set of many near-optimal ones. We show th

arXiv:2608.30186v1 Announce Type: cross Abstract: Digital twin technologies have the potential to improve operational flexibility and responsiveness capabilities of nuclear systems. To provide decisio

Today, we’re bringing ChatGPT closer to the systems, information, and workflows healthcare teams already rely on. ♥️ We’re introducing a new EHR integration to connect supported Epic environments to C

arXiv:2608.30394v1 Announce Type: cross Abstract: Existing GNN quantization methods suffer from considerable quantization overhead, which severely limits their practical usage in real-world scenarios.

arXiv:2608.31013v1 Announce Type: cross Abstract: Designing models that generalize effectively in low- to medium-data regimes remains a primary challenge in medical machine learning, particularly for

arXiv:2608.30899v1 Announce Type: new Abstract: Most trajectory forecasting models are trained on clean annotated histories, and are often evaluated under the same idealized assumption, although pract

arXiv:2601.18552v2 Announce Type: replace Abstract: LLMs expand accessibility and provide wide-reaching access to information. Yet these interactions also create opportunities to embed subtle, goal-or

arXiv:2608.29227v1 Announce Type: new Abstract: In this work we propose a novel non-linear diffusion filtering approach for images based on their channel representation. To derive the diffusion update

arXiv:2603.23947v2 Announce Type: replace-cross Abstract: Audio fingerprinting converts audio to much lower-dimensional representations, allowing distorted recordings to still be recognized as their o

arXiv:2608.30054v1 Announce Type: cross Abstract: When does 3D Gaussian Splatting (3DGS) recover the true scene surface rather than just overfitting view-dependent appearance? We answer this by develo

arXiv:2608.30502v1 Announce Type: new Abstract: Machine learning systems are increasingly corrected while they run, and the decision of when to intervene is increasingly delegated to statistical monit

arXiv:2608.27821v1 Announce Type: new Abstract: Explainable artificial intelligence (XAI) increasingly calls for actionable counterfactual recourse, yet current methodologies face challenges related t

An account from a level-headed economist who was not worried about AI but now is worried because of the Hugging Face Incident I think it is very hard to ignore the fact that cybersecurity will become

arXiv:2608.28329v1 Announce Type: new Abstract: Medical question answering (QA) systems have become crucial tools for providing reliable health information. But they remain very unexplored for low-res

arXiv:2608.27497v1 Announce Type: new Abstract: Recent embodied models increasingly leverage geometric representations to improve spatial reasoning and robotic manipulation. However, existing reconstr

arXiv:2608.28570v1 Announce Type: new Abstract: Identifying the underlying dynamics and 3D geometry of deformable linear objects (DLOs), such as cables, ropes, and hoses, is essential for accurate rob

arXiv:2608.28142v1 Announce Type: new Abstract: Electrification of commercial delivery fleets is shifting fleet routing from distance- and time-based optimization toward energy-aware decision-making.

arXiv:2608.27634v1 Announce Type: cross Abstract: Nearest neighbor classification relies fundamentally on how locality is defined, yet conventional k-NN imposes the same neighborhood cardinality throu

arXiv:2608.27516v1 Announce Type: cross Abstract: Deep learning's diagnostic utility in pathology is constrained by model vulnerability to real-world data imperfections. While current strategies favor

arXiv:2608.27967v1 Announce Type: cross Abstract: The timely dissemination of cyber threat intelligence (CTI) is critical for organizations to mount swift and effective incident response. When valid C

arXiv:2608.28237v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) models are increasingly deployed in dynamic environments where concept drift causes the underlying process distribut

Enterprise infrastructure strategy is being rewritten around the private AI cloud, as security exposure, spiking hardware prices and rising token costs push artificial intelligence workloads back insi

Even if you aren't interested, you should read an account of the Hugging Face Incident updated with what we learned last week, it is really eye opening about AI. If not mine then read the more detaile

Excited to welcome @greptile, the AI code reviewer trusted by 11,000+ teams, as a Together AI customer. Greptile's agents review and test pull requests with full context of your codebase, and running

arXiv:2608.28218v1 Announce Type: new Abstract: Vision-language models (VLMs) are rapidly progressing and offer promising capabilities for assistive technologies supporting persons with blindness or l

Enterprise experimentation with cloud AI has run into a wall of data-control, sovereignty and token-cost questions, pushing intelligence back toward infrastructure enterprises own. The result is a reb

Its kind of a bummer that Asimov's Three Laws of Robotics do not work for actual AI morality. But the failure shows why rule-based approaches won't work. (and Asimov wanted to write stories about how

As AI adoption accelerates and language models become commodities, enterprises are discovering that knowledge graphs provide the critical layer for turning scattered data into usable, real-time contex

arXiv:2608.28273v1 Announce Type: new Abstract: Urban transportation systems consist of multiple mobility modes that coexist within the same city and exhibit complex interdependencies, leading to corr

arXiv:2602.17654v2 Announce Type: replace-cross Abstract: Embedding-based retrieval (EBR) for large-scale e-commerce search faces three intertwined challenges: graded (non-binary) relevance where enga

arXiv:2608.27500v1 Announce Type: cross Abstract: Network comparison using optimal transport is a growing area of research in network science. Unlike standard graph metrics, optimal transport computes

arXiv:2504.04342v2 Announce Type: replace Abstract: Scaling up model parameters and training data consistently improves the performance of large language models (LLMs), but at the cost of rapidly grow

arXiv:2608.27574v1 Announce Type: new Abstract: Multi-label graph learning intends to capture the intrinsic complexity of real-world applications, where one sample is often related to multiple groups

arXiv:2608.28568v1 Announce Type: new Abstract: Sign language production (SLP) aims to generate continuous signing motion from spoken language, often through gloss-to-pose generation. Prior work mainl

arXiv:2603.16621v2 Announce Type: replace Abstract: We propose a conjugate and calibrated Gaussian process (GP) model for multi-class classification by exploiting the geometry of the probability simpl

arXiv:2608.28270v1 Announce Type: new Abstract: We present a real-time semantic navigation framework for Unmanned Aerial Vehicles (UAVs) focused on improving time efficiency in the Object Goal Navigat