SegDem: Segmentation helps Demosaicing
arXiv:2608.07916v1 Announce Type: new Abstract: Image demosaicing reconstructs a full-color image from incomplete color measurements produced by a sensor covered with a color filter array (CFA). Most
Knowledge catalogue
arXiv:2608.07916v1 Announce Type: new Abstract: Image demosaicing reconstructs a full-color image from incomplete color measurements produced by a sensor covered with a color filter array (CFA). Most
arXiv:2510.15968v2 Announce Type: replace-cross Abstract: Thermal management in 3D ICs is increasingly challenging due to higher power densities. Traditional PDE-solving-based methods, while accurate,
arXiv:2608.08685v1 Announce Type: new Abstract: Reliable semi-dense matching is essential for modern geometric vision systems. Designed under a coarse-to-fine paradigm, it achieves an optimal balance
arXiv:2608.09400v1 Announce Type: cross Abstract: Research regarding the sign language recognition mostly relies on RGB images, whileas sign language datasets that provide depth images are limited. Po
arXiv:2601.19180v2 Announce Type: replace-cross Abstract: Inversion-free image editing using flow-based generative models challenges the prevailing inversion-based pipelines. However, existing approac
arXiv:2608.09271v1 Announce Type: cross Abstract: Group-based reinforcement learning objectives such as GRPO can allocate learning signal poorly across prompt difficulty: under binary rewards, group n
arXiv:2608.08984v1 Announce Type: new Abstract: Model selection for imbalanced binary classification often uses the Matthews correlation coefficient (MCC), but thresholding makes validation rankings t
arXiv:2603.22213v2 Announce Type: replace-cross Abstract: While large language models (LLMs) are pretrained on massive amounts of data, their knowledge coverage remains incomplete in specialized, data
arXiv:2608.09887v1 Announce Type: new Abstract: Ball possession is the most-cited and most-misleading number in football: 60% recycled in one's own half is not 60% spent pinning the opponent back. Exi
arXiv:2608.08321v1 Announce Type: new Abstract: Floods and landslides often co-occur, but their relationships with environmental controls vary spatially. This study develops a spatial heterogeneity-aw
arXiv:2508.04224v2 Announce Type: replace Abstract: Reconstructing dynamic 3D scenes from monocular video remains fundamentally challenging due to the need to jointly infer motion, structure, and appe
arXiv:2608.07618v1 Announce Type: cross Abstract: Stochastic gradient descent for a loss function discontinuous across lower dimensional manifolds is analyzed by studying its differential equation lim
arXiv:2307.10053v5 Announce Type: replace-cross Abstract: In this paper, we focus on providing convergence guarantees for stochastic subgradient methods in minimizing nonsmooth nonconvex functions. We
arXiv:2608.09190v1 Announce Type: new Abstract: GK is a query-directed first-order prover that extends ordinary resolution-based proof search with explicit positive and negative claims, numerical conf
arXiv:2608.09767v1 Announce Type: new Abstract: Real-time MRI makes it possible to observe vocal-tract articulation during speech, but mapping these articulatory patterns to phonetic and phonological
arXiv:2608.08115v1 Announce Type: new Abstract: Point cloud completion commonly follows a coarse-to-fine paradigm, where a low-density coarse shape is first predicted and then upsampled to the target
arXiv:2608.08479v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) offer a promising pathway to energy-efficient AI and brain-inspired computing. However, their widespread adoption is hi
arXiv:2608.08103v1 Announce Type: new Abstract: Smooth acyclicity constraints answer whether a weighted support is a DAG, whereas structure learning asks which support change should be made. Existing
arXiv:2608.00417v2 Announce Type: replace Abstract: Although large language models (LLMs) can produce fluent spatial reasoning traces, their intermediate relations may fail to support the final conclu
arXiv:2608.09731v1 Announce Type: new Abstract: Wireless telerobotic manipulation relies on timely multi-view video feedback, but the available uplink bandwidth is often limited and dynamic. This pape
arXiv:2608.09264v1 Announce Type: new Abstract: Magnetic field strength is a major source of domain shift in magnetic resonance imaging (MRI), affecting signal-to-noise ratio, tissue contrast, spatial
arXiv:2608.09590v1 Announce Type: new Abstract: Learning reliable correspondences between images and point clouds is fundamental for 2D-3D matching. Despite recent progress in detection-free methods,
arXiv:2601.21747v4 Announce Type: replace-cross Abstract: Sepsis remains one of the most complex and heterogeneous syndromes in intensive care. While deep learning models achieve competitive performan
arXiv:2608.09351v1 Announce Type: cross Abstract: Test-time scaling improves LLM accuracy but multiplies inference cost, making the accuracy gained per unit of compute the metric that matters in deplo
arXiv:2608.09706v1 Announce Type: cross Abstract: Large language models can write parametric CAD programs from a natural-language description (text-to-CAD generation), but a single sample is often wro
arXiv:2507.10810v3 Announce Type: replace Abstract: We examined how social approval motivates online hate via the social approval theory, which argues social approval signals on hate messages predict
arXiv:2601.03100v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) typically rely on a single late-layer feature from a frozen vision encoder, leaving the encoder's ric
arXiv:2608.09093v1 Announce Type: cross Abstract: How a document's arrangement is written down, its notation, is a training variable that no dataset card records. The field has established that text-e
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. These startups are chasing the next big thing in LLMs Nine yea
arXiv:2608.07566v1 Announce Type: new Abstract: We introduce a continuous metric field framework trained by a single causal contrastive loss. The framework encodes a scene into coefficients of a fixed
arXiv:2608.08317v1 Announce Type: new Abstract: Biological neural systems achieve high efficiency and robustness through compartmentalized architectures. In contrast, modern artificial neural networks
arXiv:2608.07737v1 Announce Type: new Abstract: This paper investigates whether the postmodern claim of unrestricted semantic indeterminacy, and its foundational Saussurean axiom of the arbitrary sign
arXiv:2606.23335v2 Announce Type: replace-cross Abstract: Provenance watermarking is increasingly treated as a safeguard for synthetic speech, whether built directly into speech-generation models such
arXiv:2608.08020v1 Announce Type: new Abstract: Test-time compute scaling is a primary driver of performance in large reasoning models (LRMs), but extreme inefficiency bounds current approaches, shift
arXiv:2511.15709v2 Announce Type: replace Abstract: Recent works have shown that tokenisation is NP-complete. However, these works assume tokenisation is applied to inputs with unboundedly large alpha
arXiv:2608.07713v1 Announce Type: new Abstract: Latent medical image generators usually treat the tokenizer as fixed preprocessing. We test whether this separation is valid in a controlled ChestMNIST
arXiv:2608.08139v1 Announce Type: new Abstract: Establishing the provenance of a language model---including its base checkpoint and possible overlap in training distributions---is a governance challen
arXiv:2608.08048v1 Announce Type: cross Abstract: This paper presents, for the first time in power systems literature to our knowledge, analytical tools to explain the training performance of machine
arXiv:2608.08919v1 Announce Type: cross Abstract: During standard radiotherapy planning, repeated CT acquisitions are often required for patient registration, verification, and adaptive planning, resu
arXiv:2608.07473v1 Announce Type: new Abstract: Evaluative AI (EAI) has been recently proposed as a way to support human decision-making, not by producing a single recommendation, but by presenting co
arXiv:2608.08446v1 Announce Type: new Abstract: Personalized generation systems retrieve user history by request--memory relevance and inject it into the model context. Yet relevant history may concer
arXiv:2608.09558v1 Announce Type: new Abstract: How expressive is prompting a transformer? Answering this question is important for separating the roles of prompting, architecture, and pretraining in
arXiv:2608.07524v1 Announce Type: new Abstract: Training deep learning models on variable long sequences poses significant computational challenges. Existing methods force a difficult trade-off betwee
arXiv:2608.09464v1 Announce Type: cross Abstract: This paper studies hidden-target localization from range-bearing packets reported by a relay beacon whose global position and yaw are unknown. The veh
arXiv:2608.08554v1 Announce Type: cross Abstract: Power amplifier (PA) nonlinearity and memory effects significantly limit the spectral compliance, reliability, and energy efficiency of communication
arXiv:2505.15662v3 Announce Type: replace-cross Abstract: We introduce Transformer-based Neural Quantum Digital Twins (Tx-NQDTs) to reconstruct the low-energy spectral evolution of many-body quantum s
arXiv:2512.08462v2 Announce Type: replace Abstract: Decoding brain states from functional magnetic resonance imaging (fMRI) data is vital for advancing neuroscience and clinical applications. While tr
arXiv:2608.09044v1 Announce Type: new Abstract: Continual self-evolution requires LLM agents to transform environmental interactions into reliable and reusable experience. Existing methods typically r
arXiv:2608.09522v1 Announce Type: new Abstract: Automated detection of subsurface cavities from Ground Penetrating Radar (GPR) is most difficult in soft, high-water-content ground, where conductive, w
arXiv:2608.08354v1 Announce Type: new Abstract: Tropical cyclones are growing more destructive in a changing climate, and efficient forecasting of their structure and track has become a necessity. Dee
arXiv:2608.08119v1 Announce Type: new Abstract: The rapid advancement of artificial intelligence (AI) has significantly accelerated research in time-series analysis, particularly in forecasting, class
arXiv:2608.09605v1 Announce Type: cross Abstract: Large Language Models (LLMs) have emerged as powerful tools for improving recommendation systems. The effectiveness of LLMs arises from their ability
arXiv:2608.08982v1 Announce Type: new Abstract: Interactive video world models generate rollouts autoregressively under an action stream, yet they are trained and evaluated almost exclusively on factu
arXiv:2608.09071v1 Announce Type: cross Abstract: Forward uncertainty propagation in complex physical systems can induce structured covariance across field-valued outputs. For a probabilistic surrogat
arXiv:2608.09198v1 Announce Type: new Abstract: Conventional robotic grippers often use high-ratio transmissions to generate grasping torque and external force sensors to measure physical interaction.
arXiv:2602.06343v3 Announce Type: replace Abstract: High-fidelity rendering of dynamic humans from monocular videos typically degrades catastrophically under occlusions. Existing solutions incorporate
arXiv:1312.0925v4 Announce Type: replace Abstract: Alternating Minimization is a widely used and empirically successful heuristic for matrix completion and related low-rank optimization problems. Theo
arXiv:2608.08676v1 Announce Type: cross Abstract: Semantic vision encoders have become a central visual interface for multimodal understanding and semantic conditioning in image generation. However, t
arXiv:2608.09630v1 Announce Type: cross Abstract: Unsupervised domain adaptation is a widespread set of methods that leverages the knowledge of a labeled source domain to train a model to perform well
arXiv:2608.08791v1 Announce Type: new Abstract: Diffusion language models use broad context to create text, suggesting they might handle input noise better than standard models. Testing reveals this i