Knowledge catalogue
arXiv:2607.05217v1 Announce Type: cross Abstract: Public institutions increasingly use large language models (LLMs) to answer citizens' questions, often pairing a curated knowledge base with live web
arXiv:2607.03171v1 Announce Type: cross Abstract: Decentralised federated learning, based on peer-to-peer communication, is increasingly proposed for on-device training of machine learning models, pro
arXiv:2607.04140v1 Announce Type: cross Abstract: Autoregressive (AR) text-to-speech (TTS) models generate discrete speech tokens sequentially, which makes inference slow and can degrade robustness by
arXiv:2607.02551v1 Announce Type: cross Abstract: Video multimodal large language models have made strong progress on open-ended video understanding, but they still lack precise local spatiotemporal p
arXiv:2607.04668v1 Announce Type: cross Abstract: On-device LLM decoding is a hard-barriered CPU-SIMD computation that wants every core for milliseconds per token, while the rest of the OS wants those
arXiv:2607.04636v1 Announce Type: new Abstract: Key Information Extraction (KIE) converts visually rich documents into structured data, but practical deployment remains challenging: strong performance
arXiv:2607.04190v1 Announce Type: new Abstract: Global reanalysis products such as ERA5-Land provide spatially complete weather fields but at resolutions too coarse for local applications, particularl
arXiv:2607.05095v1 Announce Type: new Abstract: Temporal Graph Neural Networks (TGNNs) are widely used for learning from dynamic graphs in applications such as recommendation, social network analysis,
arXiv:2607.03822v1 Announce Type: new Abstract: Vision-based 3D occupancy prediction fundamentally relies on the 2D-to-3D view transformation. Current paradigms predominantly utilize explicit physical
arXiv:2607.03334v1 Announce Type: cross Abstract: The federated learning (FL) paradigm fosters distributed pervasive computing combined with artificial intelligence techniques, allowing for optimized
arXiv:2607.02636v1 Announce Type: cross Abstract: Object detection is a fundamental capability for AI-driven perception in safety-critical drone and edge-vision systems, including disaster response, o
arXiv:2607.04085v1 Announce Type: cross Abstract: Routing-prediction federated learning has emerged as a new paradigm that reframes inter-client heterogeneity as a resource for system-level intelligen
arXiv:2512.21196v2 Announce Type: replace Abstract: Collective motion inspired by animal groups offers powerful design principles for autonomous aerial swarms. We present a bio-inspired 3D flocking al
arXiv:2607.04856v1 Announce Type: new Abstract: Local Process Models (LPMs) are an underexplored concept in process mining. LPMs describe patterns in event data considering sequence, choice, concurren
arXiv:2607.03279v1 Announce Type: new Abstract: Accurate regional weather prediction requires resolving fine-scale structure while remaining consistent with global dynamics. Traditional limited area m
arXiv:2606.18089v2 Announce Type: replace Abstract: Post-training pipelines that combine supervised fine-tuning (SFT) with reinforcement learning (RL) have emerged as the key recipe for transforming l
arXiv:2512.09423v2 Announce Type: replace Abstract: Learning natural body motion remains challenging due to the strong coupling between spatial geometry and temporal dynamics. Embedding motion in phas
arXiv:2607.03789v1 Announce Type: new Abstract: Human spatial understanding arises from jointly perceiving geometry and semantics, enabling consistent object identification and localization across vie
arXiv:2607.03817v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) show strong few-shot generalization, but industrial anomaly detection remains difficult because defects are small, input
arXiv:2607.04310v1 Announce Type: new Abstract: Optimization-based local planning and control require high-rate collision-avoidance constraint evaluation over a prediction horizon. In obstacle-dense e
arXiv:2601.13465v4 Announce Type: replace Abstract: Graph neural networks are usually treated as auxiliaries for combinatorial optimization: they imitate algorithms, guide search, or supply scores to
arXiv:2607.02719v1 Announce Type: new Abstract: Radiologists routinely compare current and prior chest X-rays to track disease progression, producing follow-up reports that describe multiple findings,
arXiv:2607.02919v1 Announce Type: cross Abstract: Magnetic particle imaging (MPI) enables real-time, radiation-free tracking of magnetic nanoparticle-coated instruments, making it highly suitable for
arXiv:2607.03324v1 Announce Type: cross Abstract: Eco-friendly energy management for artificial intelligence data centers (AIDCs) is crucial because of the significant increase in energy consumption-i
This post describes architectural patterns for building a local-first personal AI agent, covering key components including orchestration frameworks, memory systems, tool integration, LangGraph for wor
arXiv:2607.02560v1 Announce Type: new Abstract: Pedestrian-level wind prediction is essential for urban design and wind-comfort assessment, but high-fidelity simulations such as LES remain computation
arXiv:2607.02672v1 Announce Type: new Abstract: Local pairwise comparisons are a standard tool for learning how people want decision rules to work, e.g., in participatory design or alignment. However,
arXiv:2509.15908v3 Announce Type: replace-cross Abstract: Nanoporous materials hold promise for diverse sustainable applications, yet their vast chemical space poses challenges for efficient design. M
arXiv:2607.04982v1 Announce Type: cross Abstract: High-resolution velocity models are crucial for reservoir characterization and subsurface delineation. However, the band limited nature of our surface
arXiv:2606.16533v3 Announce Type: replace Abstract: We introduce extbf{Kairos}, a regret-aware native world-action model stack for Physical AI. Kairos is motivated by the view that a physical world mo
arXiv:2607.04652v1 Announce Type: new Abstract: Learning manipulation from few demonstrations requires visual priors that capture not only where to interact, but also how the interaction should begin;
arXiv:2607.04983v1 Announce Type: cross Abstract: This article is about the development of a fuzzy cognitive map using a local large language model. In the light of recent advances it is evident that
arXiv:2604.04931v2 Announce Type: replace Abstract: Local feature matching has long been a fundamental component of 3D vision systems such as Structure-from-Motion (SfM), yet progress has lagged behin
arXiv:2607.04733v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) is the standard approach for adapting pretrained language models to downstream domains, yet it often improves target-domain
arXiv:2607.03013v1 Announce Type: cross Abstract: Images captured by consumer electronic devices, such as mobile phones and digital cameras, often suffer from low-light degradation due to sensor limit
arXiv:2607.04139v1 Announce Type: new Abstract: Self-supervised learning (SSL) shows strong potential for cross-dataset transfer by improving feature representation and generalization. However, its ap
arXiv:2508.05049v1 Announce Type: cross Abstract: AI-powered medical devices have driven the need for real-time, on-device inference such as biomedical image classification. Deployment of deep learnin
arXiv:2607.04391v1 Announce Type: new Abstract: Long-term memory remains a structural weakness of AI agents. The dominant approach, retrieval-augmented generation (RAG), relies on embedding-based simi
arXiv:2607.05297v1 Announce Type: new Abstract: Recent LLM agents tackle increasingly long-horizon, open-ended tasks, and external skills, reusable procedural knowledge supplied to the agent, further
arXiv:2607.03641v1 Announce Type: cross Abstract: The manifold hypothesis posits that high-dimensional data are concentrated near a low-dimensional embedded manifold. Recent advances in mixture variat
arXiv:2607.05032v1 Announce Type: new Abstract: Background: Disease severity is a multidimensional construct difficult to capture with rule-based approaches in Electronic Healthcare Records (EHR). Age
arXiv:2607.02544v1 Announce Type: cross Abstract: DiLoCo-style training reduces communication by letting learner islands train locally before occasional outer synchronization, making it attractive for
arXiv:2607.02846v1 Announce Type: new Abstract: Large language model (LLM) agents can improve through accumulated experience, but free-form textual memories become difficult to maintain, validate, and
arXiv:2607.03213v1 Announce Type: cross Abstract: We present OpenGlass, an open-source, privacy-oriented, local-first system for low-latency multimodal visual assistance, with a primary focus on blind
arXiv:2607.03663v1 Announce Type: cross Abstract: The accurate estimation of Above-Ground Biomass (AGB) in mature tropical forests remains a critical challenge in remote sensing, primarily due to the
arXiv:2607.02537v1 Announce Type: cross Abstract: Jamming and spoofing pose significant threats to wireless and satellite navigation by disrupting radio-frequency (RF) signals and compromising availab
arXiv:2607.04478v1 Announce Type: cross Abstract: Automated chest X-ray classification remains challenging due to severe class imbalance, co-occurring pathologies, and the loss of localized features i
arXiv:2607.02986v1 Announce Type: new Abstract: Device-free 3D human pose estimation using commodity WiFi Channel State Information (CSI) enables privacy-preserving and illumination-robust human sensi
arXiv:2607.04107v1 Announce Type: new Abstract: Word surprisal is a well-established computational predictor of human neural responses during language comprehension, but it remains less clear whether
arXiv:2601.08303v3 Announce Type: replace Abstract: Recent advances in diffusion transformers (DiTs) have set new standards in image generation, yet remain impractical for on-device deployment due to
arXiv:2607.04098v1 Announce Type: new Abstract: In recent years, 4D imaging radar has gained wide attention in autonomous driving for its robustness against harsh weather and ability to output target
arXiv:2602.04356v2 Announce Type: replace Abstract: Targeted adversarial attacks on Large Vision-Language Models (LVLMs) test whether small image perturbations can steer model responses toward attacke
Gao Yuan / Bloomberg: Survey: Chinese companies plan to allocate 46% of their AI accelerator budget to domestic products in the next 12 months, up from 30% today, a shift from Nvidia — Chinese compani
arXiv:2607.02807v1 Announce Type: new Abstract: Long-running coding agents such as autoresearch can persistently discover optimizations for open-ended problems. However, they tend to converge onto a s
A chipmaker called Syntiant Corp. that specializes in making low-powered processors that run artificial intelligence locally on devices has filed to go public. The company filed its initial public off
arXiv:2607.02840v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown promising generalization in robotic manipulation, but they still struggle with contact-rich tasks, where
arXiv:2607.03347v1 Announce Type: new Abstract: We consider the Multiscale Single-Index Model (MSIM), first introduced in ite{oymak2021learning}, as a stylized model for hierarchical learning with sca
arXiv:2607.02798v1 Announce Type: new Abstract: Modern image-and-text-to-video diffusion models can synthesize highly realistic videos by iteratively denoising an initial Gaussian noise tensor conditi
arXiv:2509.22082v3 Announce Type: replace Abstract: Federated learning enables distributed information sharing and collaborative model training without exposing raw client data. However, shared gradie
arXiv:2607.02545v1 Announce Type: cross Abstract: Structural health monitoring (SHM) has emerged as an essential tool for ensuring the integrity and reliability of critical engineering structures, par