Knowledge catalogue
arXiv:2609.09185v1 Announce Type: new Abstract: Multi-label chest X-ray classification has attracted considerable attention in recent years, with the effective use of visual representations and clinic
arXiv:2609.09022v1 Announce Type: cross Abstract: AI-assisted programming raises distinct questions about who produces code, who feels ownership of it, and who is responsible when it fails. This resea
arXiv:2609.07594v1 Announce Type: cross Abstract: Conversational Task Assistants (CTAs) are multimodal dialogue systems that support users in complex real-world tasks such as cooking and DIY through v
arXiv:2609.07318v1 Announce Type: cross Abstract: Healthcare Internet of Things (HIoT) technology is revolutionising the healthcare industry by enabling real-time data collection and analysis for pers
arXiv:2609.07533v1 Announce Type: new Abstract: In data-driven predictive maintenance (PdM), feature extraction is usually treated as fixed preprocessing: a descriptor set is chosen once and reused wh
arXiv:2609.09326v1 Announce Type: cross Abstract: This article introduces PeriodicCALM, an effective real-time anomaly detection framework designed for cyclostationary data streams. While classical cy
arXiv:2609.10200v1 Announce Type: new Abstract: Integrated sensing and communication (ISAC) provides a promising foundation for beam prediction in future vehicle-to-everything (V2X) networks. However,
arXiv:2609.09564v1 Announce Type: new Abstract: The digitalisation of electrical distribution networks has increased the exposure of power-grid infrastructure to cyber attacks. Existing intrusion dete
arXiv:2405.00636v4 Announce Type: replace-cross Abstract: This study investigates the robustness of shallow graph embedding methods for community detection in the face of network perturbations, specif
arXiv:2609.10363v1 Announce Type: new Abstract: SceneHI is a framework that lifts high-resolution, illumination-aware priors from 2D diffusion models to perform 3D texture synthesis. It is the first t
Artificial intelligence is making companies into factories of intelligence. As AI becomes a new workload, it has also become a new attack surface. The factory model that enterprises are building to pr
arXiv:2609.08443v1 Announce Type: cross Abstract: Modeling long-term user behavior is central to sequential recommendation and billion-scale industrial recommender systems, yet production ranking mode
arXiv:2604.04925v3 Announce Type: replace Abstract: Generating procedural synthetic data for multi-view stereo (MVS) usually requires writing complex rules to match the realism of curated datasets. We
arXiv:2609.05928v1 Announce Type: cross Abstract: Large language models now compute correct tax liabilities on over 90% of well-formed cases in statutory benchmarks, which makes them candidates for th
arXiv:2609.08950v1 Announce Type: cross Abstract: Text-to-SQL systems translate natural language queries into executable SQL, democratizing access to structured data. Despite recent advances driven by
arXiv:2505.03380v2 Announce Type: replace Abstract: Accurate delineation of tumors and surrounding organs-at-risk is essential for radiotherapy, surgery and treatment response assessment, yet remains
arXiv:2609.09496v1 Announce Type: new Abstract: Algorithmic outputs now populate the digital environments through which contemporary life is organized. The role of law in facilitating and constituting
The strawberry thing was very funny but probably gave people the wrong impression of where AI was heading in math. Every FrontierMath Tier 4 problem has now been solved by AI, with GPT-6 Astra solving
arXiv:2609.06974v1 Announce Type: cross Abstract: Large language models achieve strong performance across diverse tasks, but deployment remains costly because of memory, latency, and energy demands. S
arXiv:2609.06840v1 Announce Type: cross Abstract: Web Application Firewalls (WAFs) mainly rely on signatures to detect known attacks, which can leave gaps against modified or previously unseen payload
arXiv:2609.05882v1 Announce Type: cross Abstract: Multi-turn interaction creates a feedback process in which an LLM's previous responses become context for later behavior. Prior work shows substantial
arXiv:2609.09402v1 Announce Type: cross Abstract: Enterprises managing large X.509 certificate inventories face a prioritization problem: deterministic analysis tools that precisely identify standards
arXiv:2609.08070v1 Announce Type: cross Abstract: The brain uses discrete spikes for dynamic computation, yet, how neural microcircuits (NMCs) solve temporal credit assignment using local spike timing
arXiv:2609.05892v1 Announce Type: new Abstract: Human demonstrations contain rich manipulation knowledge, but it remains unclear what information can be transferred effectively to robot control. Exist
arXiv:2503.00140v3 Announce Type: replace-cross Abstract: Machine learning systems deployed in distributed or federated environments are highly susceptible to adversarial manipulations, particularly a
arXiv:2603.07648v2 Announce Type: replace-cross Abstract: Recent advances in Visual-Language-Action (VLA) models have shown promising potential for robotic manipulation tasks. However, real-world robo
arXiv:2604.06589v2 Announce Type: replace Abstract: Bimanual dexterous grasping is a fundamental and promising area in robotics, yet its progress is constrained by the lack of comprehensive datasets a
arXiv:2609.07086v1 Announce Type: cross Abstract: Transformers are a dominant architecture in modern machine learning, powering applications across vision, language, and beyond. At the core of their s
arXiv:2606.13877v2 Announce Type: replace Abstract: Contact-rich manipulation requires world models to capture complex interaction dynamics from heterogeneous visual and tactile observations, yet the
arXiv:1706.04580v3 Announce Type: replace Abstract: The design and organization of complex robotic systems traditionally requires laborious trial-and-error processes to ensure both hardware and softwa
arXiv:2505.20498v3 Announce Type: replace Abstract: Vision-based tactile sensing is widely used in perception, reconstruction, and robotic manipulation, yet collecting large-scale tactile data remains
arXiv:2609.06053v1 Announce Type: new Abstract: The validation of data, such as customer and employee data, is an important task in many organizations. Errors in data can have severe consequences. For
arXiv:2609.08332v1 Announce Type: new Abstract: We present EdMCGS (Event-driven Markov chain Gaussian Splatting), an end-to-end method for reconstructing dynamic 3D scenes from extreme-low-frame-rate
arXiv:2609.07145v1 Announce Type: new Abstract: Planning six-degree-of-freedom (6-DoF) grasps for unseen objects in cluttered tabletop scenes from a single-view depth image requires accurate and effic
arXiv:2609.07893v1 Announce Type: cross Abstract: Deep learning is an efficient technique to monitor the real time welding process, reducing post-welding repairs and production delays. This paper leve
arXiv:2609.08620v1 Announce Type: cross Abstract: We address the challenge of scalable uncertainty quantification in large-scale scientific applications, where complex state-of-the-art machine learnin
arXiv:2609.08305v1 Announce Type: new Abstract: Automating filament tracing in Cryo-Electron Microscopy (Cryo-EM) is essential for 3D helical reconstruction but challenged by intersecting topologies a
arXiv:2609.07497v1 Announce Type: new Abstract: Existing SLAM systems lack modeling of the functional relations required for fine-grained robotic interaction. Functional 3D scene graphs can represent
arXiv:2609.08385v1 Announce Type: new Abstract: Floorplans are compact, appearance-invariant maps ideal for indoor localization, yet existing methods rely on depth networks that are brittle in clutter
General Robotics Technology Inc. said today that its GRID robot intelligence platform now automates its own engineering work, cutting the time needed to get a new robot into production from about a mo
arXiv:2609.07231v1 Announce Type: new Abstract: Estimating the 6D pose of textureless objects without prior CAD models remains a critical challenge due to the lack of appearance features. While recent
arXiv:2609.06016v1 Announce Type: new Abstract: Quantum clustering aims to exploit quantum feature representations to uncover complex data structures beyond conventional Euclidean geometry. Yet this s
arXiv:2609.07975v1 Announce Type: new Abstract: Bringing multiscale geometric analysis directly to irregular point clouds remains difficult: quantities such as local dimension, anisotropy, density var
arXiv:2609.08306v1 Announce Type: cross Abstract: We introduce HoneyRoute, an inference-serving layer that detects whether an incoming request is malicious and, if so, routes it to a dedicated honeypo
arXiv:2609.08685v1 Announce Type: new Abstract: Standard open-set node classification methods rely on the homophily assumption, where connected nodes share labels. However, real-world graphs are often
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: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