Knowledge catalogue
arXiv:2609.28563v1 Announce Type: new Abstract: Spatial transcriptomics (ST) profiles gene expression within tissue architecture, but its cost and experimental complexity limit routine use. Predicting
arXiv:2609.29116v1 Announce Type: new Abstract: Distribution Matching Distillation (DMD) enables high-quality diffusion sampling in only a few steps, but its optimization dynamics remain dominated by
arXiv:2609.29505v1 Announce Type: new Abstract: Diffusion inference repeatedly evaluates the same large network. We ask whether pretrained weights alone can identify residual branches that need not be
arXiv:2609.28713v1 Announce Type: cross Abstract: Self-supervised learning (SSL) countermeasures (CMs) have shown strong performance in recent years. However, they often show degraded performance whil
arXiv:2609.28502v1 Announce Type: new Abstract: Knowledge tracing (KT) models predict student performance opaquely, limiting pedagogical action. This study contributes a validation protocol testing pr
arXiv:2609.29291v1 Announce Type: cross Abstract: We propose Sufficiently Reduced Distributional Regression (SRDR), a generative method that combines conditional distribution estimation with nonlinear
arXiv:2609.29832v1 Announce Type: cross Abstract: A new method for multi-input flight maneuver design for system identification is presented. The method consists of injecting 'full-harmonic' orthogona
arXiv:2609.28747v1 Announce Type: cross Abstract: A language model's confidence in an answer is often read as a proxy for how well it knows the corresponding fact. This manual documents an open toolki
arXiv:2609.29851v1 Announce Type: cross Abstract: Behavioural biometric templates are widely believed to degrade as the gap between enrolment and verification grows, but few studies measure this templ
arXiv:2609.28716v1 Announce Type: cross Abstract: This paper investigates temporal neural networks for mbox{end-effector} position mbox{estimation} of an aerial continuum manipulator (ACM) operating u
arXiv:2609.29187v1 Announce Type: new Abstract: One of the most important problems in medicine is to facilitate prediction. In this study, we propose entropy triangle method, a novel framework for pre
arXiv:2506.20584v3 Announce Type: replace Abstract: The most popular graph indices for vector search use principles from computational geometry to build the graph. Hence, their formal graph navigabili
The US government wants to spend $30.3 million over the next five years on an improved form of lie detector, according to a Department of Defense budget request. The program, called Polygraph+ or Poly
arXiv:2609.28682v1 Announce Type: new Abstract: Post-training hybrid reasoning models in NoThink mode has attracted growing interest as a way to improve performance while keeping inference fast. Howev
arXiv:2609.29709v1 Announce Type: cross Abstract: An LLM judge scores a bank of responses against a rubric, and the reliability comes back at 0.52. What has been measured? Judge evaluation has begun b
arXiv:2609.28576v1 Announce Type: new Abstract: Historical observations are not always fixed: statistical agencies revise previously published values as new evidence arrives. Forecasting from a contem
arXiv:2609.29240v1 Announce Type: cross Abstract: Text image super-resolution (TSR) aims to recover visually faithful and readable text under unknown degradations. Existing diffusion-based methods typ
arXiv:2609.29717v1 Announce Type: new Abstract: Automated segmentation of cryo-electron tomograms routinely produces masks that are voxel-accurate but topologically broken: membranes fragment, organel
arXiv:2609.30245v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables high-quality novel-view synthesis but requires substantial storage. Existing compression methods often rely on spat
arXiv:2609.29099v1 Announce Type: cross Abstract: Multimodal training relies on image-text corpora collected from external sources, creating opportunities for attackers to poison the data. Stealthy at
arXiv:2609.30026v1 Announce Type: new Abstract: Detecting which holds a climber uses, and when, underpins automated scoring, movement analysis, and assistive systems for sport climbing. Existing appro
arXiv:2609.28654v1 Announce Type: new Abstract: Object permanence and solidity are hallmarks of human cognitive priors. Recent studies show that video generation models, a paradigmatic class of curren
arXiv:2609.29060v1 Announce Type: cross Abstract: Transformers achieve remarkable performance by jointly learning broad families of tasks during pretraining and adapting to unseen tasks from only a sh
arXiv:2609.29733v1 Announce Type: new Abstract: Arabic-language stance detection remains challenging, and previous shared-task systems have largely relied on multitask learning and ensembles. While th
arXiv:2609.26758v2 Announce Type: replace Abstract: Typed decision models are built for settings where model outputs are consumed directly by software. Instead of generating free-form text, they retur
arXiv:2609.28578v1 Announce Type: new Abstract: The increasing adoption of electric vehicles (EVs) and rooftop photovoltaic (PV) systems is reshaping residential electricity demand and creating new ch
arXiv:2508.18192v2 Announce Type: replace Abstract: Large Language Models (LLMs) have reshaped our world with significant advancements in science, engineering, and society through applications ranging
arXiv:2609.29553v1 Announce Type: cross Abstract: Automatic stress recognition from facial video provides a non-contact approach for affective monitoring. However, most existing video-based methods di
arXiv:2609.29650v1 Announce Type: new Abstract: Tabular-to-image encoding methods enable the application of models based on both convolutional neural networks and vision transformers to tabular data,
arXiv:2609.29555v1 Announce Type: new Abstract: Navigation World Models (NWMs) predict action-conditioned visual futures for planning. Two practical challenges are central to their design: selecting a
arXiv:2601.19753v2 Announce Type: replace Abstract: Underwater 3D reconstruction and appearance restoration remain challenging due to the complex optical properties of water, such as wavelength-depend
arXiv:2609.29396v1 Announce Type: new Abstract: This paper presents and evaluates a Deep Learning-based (DL-based) Signal Quality Assessment (SQA) model to distinguish between clean and noisy ambulato
arXiv:2609.29507v1 Announce Type: new Abstract: Two accounts of neural text degeneration coexist. One locates the cause in the training data -- repetition in the corpus produces repetition in the outp
arXiv:2609.28832v1 Announce Type: new Abstract: Reconstruction-based unsupervised learning can fail in two opposing ways: a model may reconstruct anomalies too accurately or discard valid nominal vari
arXiv:2609.28565v1 Announce Type: cross Abstract: Post hoc explanation methods such as SHAP and LIME are widely used to interpret text classifiers, but their visualizations are mainly designed for lef
arXiv:2609.29312v1 Announce Type: new Abstract: Communities often respond to potentially AI-assisted work by asking three questions: Was AI used? Was that use disclosed? Can hidden use be detected? Th
arXiv:2609.29048v1 Announce Type: new Abstract: Unified vision-language models (VLMs) that tokenize images through a vector-quantized (VQ) codebook routinely hallucinate objects on grounded yes/no ben
arXiv:2609.28947v1 Announce Type: cross Abstract: Misinformation is widely reported to propagate faster on engagement-based platforms, yet prior work largely focused on empirical analysis, without ide
arXiv:2609.29845v1 Announce Type: cross Abstract: While Large Language Models (LLMs) rely on highly non-linear components, in this work we demonstrate that they exhibit fundamental linearity: when inp
arXiv:2609.26923v1 Announce Type: cross Abstract: Cricket is one of the most celebrated sports world-wide, and technological advancement has become deeply embedded in how the modern game is analyzed a
arXiv:2509.10367v2 Announce Type: replace Abstract: Given a dataset of finitely many elements T = {mathbf{x}_i}_{i = 1}^N, the goal of dataset condensation (DC) is to construct a synthetic dataset S =
arXiv:2609.27139v1 Announce Type: cross Abstract: Surgical procedures follow a phase-to-step hierarchy, yet the video-language models used to recognize them are evaluated with flat per-level metrics t
arXiv:2609.27863v1 Announce Type: new Abstract: Knowledge graph completion is evaluated by ranking observed triples above randomly corrupted ones, which treats every unobserved fact as false. When the
arXiv:2609.27325v1 Announce Type: cross Abstract: In this work, we propose a hybrid iterative deep Ritz method (H-IDRM) for a class of interface problems for second-order elliptic operators. It is bas
arXiv:2609.26848v1 Announce Type: cross Abstract: Postoperative acute kidney injury (AKI) after major non-cardiac surgery carries substantial morbidity, yet early intraoperative risk stratification re
arXiv:2609.27466v1 Announce Type: new Abstract: Industrial control electronics such as programmable logic controllers, servo drives and operator panels are routinely repaired in plant maintenance, but
arXiv:2609.27240v1 Announce Type: new Abstract: In this paper, we present the Berkeley QUAD (Quasi-direct-drive, Underactuated, Asymmetric Design) Hand, a four-finger anthropomorphic robotic hand with
arXiv:2609.27866v1 Announce Type: cross Abstract: Sharing a deep encoder does not, by itself, fix the central confound of task-comparison scores. We show that cross-evaluated heads on a frozen shared
arXiv:2609.28230v1 Announce Type: new Abstract: Visual grounding in remote sensing images aims to locate objects described by referring expressions. Most existing methods predict horizontal bounding b
arXiv:2505.12576v3 Announce Type: replace-cross Abstract: A key factor in effective Self-Supervised learning (SSL) is preventing dimensional collapse, where higher-dimensional representation spaces (R
arXiv:2601.18932v2 Announce Type: replace-cross Abstract: Popularized by their strong image generation performance, diffusion and related methods for generative modeling have found widespread success
arXiv:2609.27022v1 Announce Type: new Abstract: In this paper, we investigate the impact of adversarial attacks on identity encoders within a realistic de-identification framework. Our experiments sho
This week, world leaders descended on Manhattan for the UN General Assembly. It’s also New York Climate Week—investors, policymakers, advocates, and journalists are colliding at panels, talks, and fan
arXiv:2609.27901v1 Announce Type: new Abstract: Video is a rich representation of a physical event, capturing appearance, geometry, motion, and temporal evolution. Other modalities, such as 3D body mo
arXiv:2609.21798v1 Announce Type: cross Abstract: Architectures with periodic activation functions have already been shown to be beneficial in comparison to monotonic counterparts for a wide range of
arXiv:2609.27015v1 Announce Type: new Abstract: We developed an anatomy-aware deep learning framework to synthesize post-contrast breast MRI from pre-contrast images, emphasizing tumor and background
arXiv:2609.27038v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring assumes that the reasoning a model writes reflects the computation that directly produces its answer. Previous faithfu
arXiv:2609.27371v1 Announce Type: cross Abstract: Generative image models can produce highly realistic images, raising concerns about potential misuse in creating deceptive content. Current deepfake a
arXiv:2609.27373v1 Announce Type: new Abstract: Recurrent language models repeatedly apply shared network blocks to refine latent representations, but standard inference recomputes global attention at
arXiv:2609.26868v1 Announce Type: new Abstract: Learning-based models (e.g., visuomotor and Vision-Language-Action (VLA)) are increasingly explored for industrial robotic manipulation, where model pre