Knowledge catalogue
arXiv:2607.03934v1 Announce Type: new Abstract: Motor impairments, including tremor, bradykinesia, gait abnormalities, and postural instability, are common across many neurological and movement-relate
arXiv:2506.09740v2 Announce Type: replace-cross Abstract: Diffusion models excel at image generation. Recent studies have shown that these models not only generate high-quality images but also encode
arXiv:2508.16239v2 Announce Type: replace Abstract: Quantitative microstructural characterization is fundamental to materials science, and electron micrographs (EMs) provide indispensable high-resolut
arXiv:2607.03752v1 Announce Type: cross Abstract: Measuring the extent to which emergent languages encode the visual content of their inputs is an open problem. We refer to this property as visual ref
arXiv:2607.04490v1 Announce Type: new Abstract: Facial expression recognition (FER) is crucial for social interaction in mixed reality environments that employ head-mounted displays (HMD). However, co
arXiv:2607.04069v1 Announce Type: cross Abstract: Cardiac cine Magnetic Resonance Imaging (MRI) is a critical diagnostic tool that provides dynamic insights for radiologists. To accelerate acquisition
arXiv:2607.04862v1 Announce Type: new Abstract: Accurate extreme precipitation forecasting is critical for disaster mitigation but remains challenging for numerical weather prediction (NWP) models due
arXiv:2506.05716v2 Announce Type: replace-cross Abstract: Deep Q-Networks (DQN) can suffer from overestimation bias because bootstrapped targets use a maximisation operation over noisy value estimates
arXiv:2607.03568v1 Announce Type: cross Abstract: Objective: Accurate identification of acute ischemic infarcts on diffusion-weighted magnetic resonance imaging (DWI) is a critical prerequisite for re
arXiv:2603.23669v2 Announce Type: replace-cross Abstract: Accurate estimation of forest biomass, a major carbon sink, relies heavily on tree-level traits such as height and species. Unoccupied Aerial
arXiv:2607.04872v1 Announce Type: cross Abstract: Reasoning temporal localization (RTL) requires a model to generate an answer that itself contains the time interval supporting it, so high-level reaso
arXiv:2512.22240v5 Announce Type: replace-cross Abstract: Machine learning models are primarily judged by predictive performance, especially in applied genomics, where explanations are read as biologi
arXiv:2503.10496v2 Announce Type: replace-cross Abstract: Modeling natural phenomena with artificial neural networks (ANNs) often provides highly accurate predictions. However, ANNs often suffer from
arXiv:2606.16302v2 Announce Type: replace Abstract: Rapid and accurate flood prediction is essential for disaster response and mitigation planning. Synthetic Aperture Radar (SAR) sensors in satellites
arXiv:2607.04548v1 Announce Type: cross Abstract: Novel category discovery aims to identify unseen classes from unlabeled data by transferring knowledge from labeled categories, but most existing meth
arXiv:2607.03703v1 Announce Type: new Abstract: Reinforcement Learning (RL) has emerged as a powerful paradigm for adaptive traffic signal control. However, in safety-critical infrastructure like traf
arXiv:2607.03110v1 Announce Type: new Abstract: Multi-Exposure Fusion (MEF) effectively extends dynamic range, but practical deployment is hindered by motion-induced ghosting and the scarcity of high-
arXiv:2508.04928v5 Announce Type: replace-cross Abstract: We propose a method to extend foundational monocular depth estimators (FMDEs), trained on perspective images, to fisheye images. Despite being
arXiv:2607.03180v1 Announce Type: new Abstract: Multimodal diffusion transformers (MM-DiTs) have emerged as the prevalent backbone for modern text-to-image generation systems. However, they exhibit cr
arXiv:2508.02641v2 Announce Type: replace-cross Abstract: Molecular crystal structure prediction (CSP) is essential for applications in pharmaceuticals and organic electronics. However, CSP remains ch
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:2607.04449v1 Announce Type: new Abstract: Field-boundary maps support crop monitoring, irrigation planning, and yield estimation, but many smallholder parcels span only a few 10 m Sentinel-2 pix
arXiv:2607.05201v1 Announce Type: new Abstract: In non-stationary streaming environments, simultaneously adapting to complex, non-linear domain shifts via continual learning while mitigating the catas
arXiv:2607.04096v1 Announce Type: new Abstract: Current agentic workflows usually involve decomposing user requests into sequences of tool calls with correctly resolved parameters, the results of whic
arXiv:2607.04330v1 Announce Type: new Abstract: Autonomous vehicles often rely on high-definition (HD) maps for navigation; however, these maps are not frequently updated and often lack semi-static in
arXiv:2607.05396v1 Announce Type: cross Abstract: Real-world robot deployment rarely maintains the training-stage camera setup, where cameras often experience repositioning or remounting depending on
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:2607.03325v1 Announce Type: cross Abstract: We present an automated pipeline that decomposes Italian tax-court judgments into individual legal issues and extracts, for each issue, a structured X
arXiv:2607.04691v1 Announce Type: new Abstract: While controllable image generation has made significant strides by incorporating visual reference conditions, existing methods predominantly operate as
arXiv:2607.02574v1 Announce Type: cross Abstract: The key-value (KV) cache has become a first-order memory object in LLM serving rather than a temporary per-request tensor. This survey classifies more
arXiv:2607.02977v1 Announce Type: new Abstract: Diffusion-based motion planners have demonstrated strong performance in generating diverse and high-quality robot trajectories in cluttered environments
arXiv:2607.02612v1 Announce Type: cross Abstract: Vision Transformers achieve strong image classification accuracy but process all image regions with nearly the same computation, even when many region
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:2607.04607v1 Announce Type: cross Abstract: The rapid advancement of AI-generated videos poses increasing security risks and calls for robust detectors with strong cross-domain generalization. A
arXiv:2512.17547v2 Announce Type: replace Abstract: 3D Gaussians have become a powerful scene representation for real-time splatting and high-quality novel-view synthesis. This has motivated generaliz
arXiv:2607.05369v1 Announce Type: cross Abstract: For robots to work reliably in commercial and industrial applications, can recent advances in agentic coding systems combine interpretable robot progr
arXiv:2607.05241v1 Announce Type: new Abstract: Neuromorphic visuo-tactile sensing offers a promising paradigm for low-latency and low-power robotic perception. However, existing systems still rely he
arXiv:2601.06550v3 Announce Type: replace-cross Abstract: Semantic Multi-Object Tracking (SMOT) is evolving from purely geometric localization toward comprehensive video understanding. However, existi
arXiv:2607.04440v1 Announce Type: cross Abstract: Seismic wavefield simulation is fundamental to seismology, but conventional finite-difference (FD) methods remain limited by numerical dispersion and
arXiv:2607.04500v1 Announce Type: new Abstract: Self-supervised latent world models can assign a surprise score to driving scenarios without any human labels. A natural follow-up question is whether s
arXiv:2607.03760v1 Announce Type: new Abstract: The deployment of large-scale foundation models like Segment Anything Model (SAM) on resource-constrained Earth observation platforms is hindered by pro
arXiv:2607.03931v1 Announce Type: cross Abstract: Whole-body fluorodeoxyglucose positron emission tomography combined with computed tomography is widely used in cancer care, but manual lesion delineat
arXiv:2607.04634v1 Announce Type: new Abstract: In heterogeneous robot swarms, caste reassignment (rebinding a robot to a new capability-bound role) is a high-frequency runtime event driven by battery
arXiv:2607.03709v1 Announce Type: new Abstract: Writing a literature review requires a deep understanding of the relationships among cited papers: how they build on, challenge, or offer alternative pe
arXiv:2607.03330v1 Announce Type: new Abstract: Quantifying plant growth dynamics from sparse longitudinal 3D observations is fundamental for agriculture and plant sciences. Yet, plants pose unique ch
arXiv:2607.02592v1 Announce Type: new Abstract: On-policy distillation (OPD) has recently emerged as an effective post-training paradigm by providing supervision on student-generated trajectories. How
arXiv:2607.03422v1 Announce Type: new Abstract: Recovering online pen trajectories from offline handwriting images, often referred to as handwriting trajectory recovery (stroke recovery), is an offlin
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:2607.03935v1 Announce Type: new Abstract: Self-evolving frameworks usually optimize task solutions while treating the surrounding harness as fixed. We introduce Harness-Aware Self-Evolving (HASE
arXiv:2607.04353v1 Announce Type: cross Abstract: Hierarchical structure is common in image data, where fine-grained clusters often merge into larger, coarser semantic groups. In biological cell image
arXiv:2607.04562v1 Announce Type: new Abstract: Large language models (LLMs) generate fluent outputs that can be wrong. Unlike humans, who often exhibit cues when providing false information, LLMs pro
arXiv:2607.04625v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) streamlines long-document understanding by leveraging retrieval mechanisms to restrict input images to a highly c
arXiv:2607.04302v1 Announce Type: cross Abstract: We present HiFA4, a post-training operator-level design that executes both QK^T and PV in FlashAttention as 4-bit HIF4 Cube GEMMs for LLM inference on
arXiv:2607.05329v1 Announce Type: new Abstract: Siamese verification networks are widely used to compare items such as faces, cars, or signatures. In these scenarios, the network is trained to learn a
arXiv:2607.02559v1 Announce Type: new Abstract: Automated image recognition is increasingly used to scale ecological monitoring beyond manual annotation, yet ecologists lack evidence-based guidance on
arXiv:2607.03436v1 Announce Type: new Abstract: Routing among large language models (LLMs) promises better quality at lower cost, motivated by the reported gap between learned routers and a per-instan
arXiv:2603.22730v2 Announce Type: replace Abstract: Pfeffer, Krugel, and Uhl (2025) report that OpenAI's reasoning model o1-mini produces more utilitarian responses to the trolley problem and footbrid
arXiv:2607.03025v1 Announce Type: new Abstract: The use of Large Language Models (LLMs) across diverse areas of human activity-ranging from everyday tasks to safety-critical applications-aims to enhan
arXiv:2607.04884v1 Announce Type: new Abstract: We present HunyuanOCR-1.5, a lightweight end-to-end OCR-specialized vision-language model. HunyuanOCR unifies document parsing, text spotting, informati
arXiv:2607.04811v1 Announce Type: new Abstract: Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and qualit