Knowledge catalogue
arXiv:2609.06131v1 Announce Type: cross Abstract: Environmental identification in wireless sensing is essential for 6G integrated sensing and communication (ISAC) systems to achieve reliable situation
arXiv:2310.16295v2 Announce Type: replace-cross Abstract: Neural network have achieved remarkable successes in many scientific fields. However, the interpretability of the neural network model is stil
arXiv:2609.07298v1 Announce Type: new Abstract: 3D reconstruction typically strives for geometric fidelity or visual plausibility. Radio frequency digital twins (RFDT) are instead judged by whether co
arXiv:2609.08622v1 Announce Type: new Abstract: Predictive process monitoring aims at forecasting various aspects of running processes. Among the different tasks, next activity prediction represents t
arXiv:2609.07274v1 Announce Type: cross Abstract: SLAM systems based on 3D Gaussian Splatting (3DGS) have recently demonstrated promising reconstruction accuracy for dense 3D scene representations. Ho
Machine learning doesn't end when the model is trained. You still need to evaluate it, deploy it, and build the infrastructure to keep it working in production. Today's Deal of the Day takes you acros
arXiv:2609.06959v1 Announce Type: new Abstract: 3D point cloud semantic segmentation is essential for real-world spatial understanding, yet the prohibitive cost of human annotations motivates unsuperv
arXiv:2609.09062v1 Announce Type: new Abstract: We present a real-world case study of multi-task learning (MTL) for temporal process modeling from limited data with temporally sparse labels. Specifica
arXiv:2609.06521v1 Announce Type: new Abstract: Oversmoothing is a well-known failure mode of Graph Neural Networks (GNNs). However, most existing diagnostics rely on global aggregation measures that
arXiv:2609.08159v1 Announce Type: new Abstract: Long-horizon target navigation requires a robot to sustain task execution across evolving observations, decisions, and physical interactions. This requi
arXiv:2609.07398v1 Announce Type: new Abstract: World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Ex
arXiv:2609.05918v1 Announce Type: new Abstract: We present PAI-Actor, a cinematic multi-character animation framework for character replacement in dynamic movie scenes. Unlike conventional animation s
arXiv:2511.09057v4 Announce Type: replace Abstract: A world model is a cognitive simulator of the real-world environment allowing biological agents to reason about how the world evolves, whether spont
arXiv:2609.07623v1 Announce Type: cross Abstract: Dot maps, which visualize individual data points as dots over a geographic region, are widely used across diverse domains to represent spatial pattern
arXiv:2609.07206v1 Announce Type: new Abstract: Trajectory representation learning underpins a wide range of trajectory analytics tasks; however, most existing self-supervised approaches, whether disc
arXiv:2609.07230v1 Announce Type: new Abstract: This paper propose a robust decentralized federated distillation method that enables clients with heterogeneous models to collaborate through prediction
arXiv:2410.09563v2 Announce Type: replace Abstract: In the domain of computer vision, optical flow stands as a cornerstone for unraveling dynamic visual scenes. However, the challenge of accurately es
arXiv:2609.06468v1 Announce Type: new Abstract: K-Means is one of the most widely used clustering algorithms, but its susceptibility to initial centroid selection remains a primary bottleneck for its
arXiv:2609.06109v1 Announce Type: new Abstract: Port flood digital twins require analytics that warn operators before disruption, but official warning incidents are often few and adjacent observations
arXiv:2609.07064v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have achieved strong performance on diverse visual tasks, yet their ability to reconstruct and reason about the 3D
arXiv:2609.07165v1 Announce Type: new Abstract: Learning-by-Demonstration (LbD) enables intuitive robot programming by capturing expert skills, which is crucial for agility in high-mix, low- volume ma
arXiv:2609.08412v1 Announce Type: new Abstract: Machine-learning weather models (MLWMs) now match or outperform operational numerical weather prediction (NWP) at global medium-range forecasting, at fa
arXiv:2601.13713v2 Announce Type: replace-cross Abstract: Software testing is crucial for ensuring the correctness and reliability of software systems. Automated generation of issue reproduction tests
arXiv:2609.09158v1 Announce Type: new Abstract: We study the problem of navigating cluttered indoor environments with a humanoid robot. Unlike conventional methods that model navigation as a 2D path p
arXiv:2609.07184v1 Announce Type: cross Abstract: We present tensor network representations for discrete maximum entropy distributions under expectation constraints. To this end, we introduce Computat
arXiv:2505.04376v2 Announce Type: replace-cross Abstract: LiDAR-based perception plays a fundamental role in modern robotic systems for environment understanding and navigation. Single-photon LiDAR (S
arXiv:2609.08659v1 Announce Type: new Abstract: Onboard object detection in Earth observation is constrained by limited computational resources and the absence of fully corrected imagery. While convol
arXiv:2609.06785v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection remains a fundamental challenge for neural networks, whose predictions can be overconfident on inputs that deviate f
arXiv:2411.08727v2 Announce Type: replace Abstract: Robots in human-centered environments require accurate scene understanding to perform high-level tasks effectively. This understanding can be achiev
1Password uses Codex across software delivery; its OpenAI case study reports 20.9% higher engineering productivity in a core cohort.
John Koetsier / Forbes: Antioch, which creates high-fidelity simulations to reduce the need for hardware validation in physical AI training, raised a $32M Series A led by Greylock — Figure AI pulled t
OpenAI has fully rolled out the Astra feature to all paid tiers—Plus, Pro, Business, and Enterprise—in both Codex and ChatGPT Work. The company invites users to build with Astra and highlights a live
Is the @METR_Evals long horizons measure effectively saturated? No updates to the most famous graph of AI progress since May, but other published work suggests you can effectively get 18+ weeks of wor
This is a big one. (And yes, the fights over academic credit and what happened when in the race for the proof need to be resolved, but it is still a big one.) We’re sharing a solution to the Navier-St
very relevant to today’s drama! and PSA for anyone working on anything sensitive. Synthetic data derived from production user data of consumer AI tools is used for training. I’ve heard this rumour fro
arXiv:2609.05146v1 Announce Type: new Abstract: This study introduces an intelligent framework that integrates machine learning and deep neural network ensemble techniques for early detection and prog
arXiv:2609.04772v1 Announce Type: new Abstract: The high training cost of Graph Neural Networks (GNNs) has raised growing concerns regarding model ownership infringement, such as model stealing and un
arXiv:2609.05066v1 Announce Type: cross Abstract: As the scale of video surveillance data outpaces manual annotation capacities, weakly supervised video anomaly detection (WSVAD) has emerged as a crit
arXiv:2406.02465v2 Announce Type: replace-cross Abstract: Can pretrained models generalize to new datasets without any retraining? We deploy pretrained image models on datasets they were not trained f
arXiv:2609.05063v1 Announce Type: cross Abstract: When a customer adds a professional camera to their cart, should the system suggest a matching lens, a generic tripod, or another camera body? Complem
arXiv:2609.05150v1 Announce Type: cross Abstract: This paper introduces Regime-aware Constraint-Based and Noise-Based causal discovery with Markov Blankets (RCBNB-MB), a novel causal discovery algorit
arXiv:2609.04377v1 Announce Type: new Abstract: Enterprise AI deployments fail not from model inadequacy, but because organizations lack a structured substrate encoding how they decide, negotiate, and
arXiv:2609.04690v1 Announce Type: cross Abstract: Multimodal emotion recognition has attracted growing interest due to its importance in human-computer interaction, remote education, and healthcare. T
Excited to build alongside this incredible community @KanishkaNarayan 🇬🇧 More AI jobs, investment and support, especially for young people not in education, employment and training. Welcome to the UK
arXiv:2609.04512v1 Announce Type: cross Abstract: Oral potentially malignant disorders (OPMDs) are critical precursors to oral cancer, yet clinical detection remains challenging because of substantial
arXiv:2609.05325v1 Announce Type: new Abstract: Achieving robust SLAM in large-scale underground coal mines with complex structures and severe degeneracies remains highly challenging. Dense smoke and
arXiv:2510.07314v4 Announce Type: replace-cross Abstract: Nuclear fusion plays a pivotal role in the quest for reliable and sustainable energy production. A major roadblock to viable fusion power is u
It is less than a decade since the development of the transformer. Less than four years since the release of GPT-3.5 (ChatGPT). Less than two years since the release of o1-preview (the first Reasoner)
arXiv:2609.05296v1 Announce Type: new Abstract: Does a simplified legal clause still say what the original said? The checks in current use cannot establish that it does: requiring an identical pair to
arXiv:2609.04840v1 Announce Type: new Abstract: Long-horizon predictive maintenance requires models to distinguish slowly evolving degradation from normal operating-regime variation over planning wind
arXiv:2609.04775v1 Announce Type: new Abstract: Industrial anomaly detection faces two engineering bottlenecks: memory bank construction latency and inference efficiency. Traditional sampling algorith
arXiv:2609.05136v1 Announce Type: new Abstract: Time series data is very common in many real-world applications and in numerous domains, with increasing interest for automated information extraction u
arXiv:2609.04607v1 Announce Type: new Abstract: Three-dimensional scene graphs (3DSGs) have emerged as a promising approach for building geometrically grounded, semantically informed, hierarchical gen
arXiv:2609.05212v1 Announce Type: cross Abstract: Forecasting time series accurately is critical for applications with complex data ranging from energy systems to healthcare and finance. Among current
Replit is officially in London. 🇬🇧 As we open our first international office here today, we’re honored to mark this important milestone with @MayorofLondon, Sadiq Khan and his team, His Majesty’s Gove
arXiv:2609.04931v1 Announce Type: new Abstract: The widespread adoption of artificial intelligence (AI) within real-world applications has raised a lot of concerns regarding their trustworthiness, esp
Some claim that AGI is here now. Ridiculous. No AGI without mastery of the real world! No true self-improvement without self-improving hardware, as opposed to the already existing, self-improving, met
arXiv:2510.11839v3 Announce Type: replace Abstract: Time series are ubiquitous in many applications that involve forecasting, classification and causal inference tasks, such as healthcare, finance, au
arXiv:2609.04707v1 Announce Type: cross Abstract: Wireless foundation models (WFMs) have emerged as a promising approach for learning reusable representations from large-scale wireless data and adapti
At its first Horizon customer and partner event this week, Equinix Inc. argued that the architecture of enterprise artificial intelligence is being reshaped by a simple yet hard-to-answer question: Wh