Knowledge catalogue
arXiv:2609.12004v1 Announce Type: cross Abstract: We propose a learning procedure for system identification in interacting particle systems from single-snapshot observations of collective behaviors, u
arXiv:2606.14957v4 Announce Type: replace Abstract: Brain MRIs are routinely acquired as multiple complementary sequences with unique contrast weighting, including T1-weighed imaging (T1w) anatomic an
arXiv:2609.12024v1 Announce Type: cross Abstract: Optimal transport gives structured data a geometry, but exact evaluation is costly in large pairwise analyses that exploit relationships among distanc
arXiv:2609.12915v1 Announce Type: new Abstract: Large-scale multi-label text classification assigns a small subset of relevant labels to each document from a vocabulary containing thousands or tens of
arXiv:2504.04903v3 Announce Type: replace Abstract: We present Lunima-OmniLV (abbreviated as OmniLV), a universal multimodal multi-task framework for low-level vision that addresses over 100 sub-tasks
arXiv:2602.21223v2 Announce Type: replace Abstract: It is not only what we ask large language models (LLMs) to do that matters, but also how we ask them. Phrases like ``This is urgent'' or ``As your s
arXiv:2609.12367v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) are the standard tool for auditing the privacy risks of machine learning models. Given a query point, an MIA aims
arXiv:2609.12850v1 Announce Type: new Abstract: Accurate head modeling requires a stable yet expressive geometric representation. Existing Gaussian-based head avatars commonly rely on parametric templ
arXiv:2609.12771v1 Announce Type: cross Abstract: Cross-vehicle federated learning enables vehicles to collaboratively improve perception models while keeping locally collected driving data private. H
arXiv:2609.12435v1 Announce Type: new Abstract: Post-treatment MRI in patients with glioma provides serial observations for updating patient-specific tumor-state proxy estimates, but variable appearan
arXiv:2609.12144v1 Announce Type: cross Abstract: AI-native 6G networks have brought Intent-Based Networking (IBN) to the forefront, enabling high-level goals to be translated into network configurati
arXiv:2606.18524v2 Announce Type: replace Abstract: Looped (weight-tied) Transformers apply a shared residual block N times (h leftarrow h + arepsilon,f(h), same f at each step), increasing effective
arXiv:2506.23010v2 Announce Type: replace-cross Abstract: Mean-field characterizations of first-order iterative algorithms -- including Approximate Message Passing (AMP), stochastic and proximal gradi
One thing will defeat the AI Doomers easily: Time. Little by little things will change and AI will diffuse into everyday people's lives and they'll realize it wasn't the scary bedtime story Harry Pott
I have created a VAE model using PyTorch on White Wine dataset. Basically, the main goal is to discover a brand-new white wine recipe. It puts all the wines into a latent space, finds the best part wh
arXiv:2609.12902v1 Announce Type: new Abstract: Artificial intelligence has shown promise in assisting radiologists in imaging-based diagnosis across a wide range of diseases. Efficient training of la
arXiv:2609.12224v1 Announce Type: new Abstract: Electronic health records (EHRs) may incompletely capture patient-reported factors associated with opioid use disorder (OUD). We evaluated whether surve
arXiv:2403.05864v3 Announce Type: replace Abstract: In human-centric Cyber-Physical Systems (CPS), personalized Deep Reinforcement Learning (DRL) agents must share fine-grained control actions with cl
I'm starting a PhD where I will be doing Graph ML (somewhere along the lines of graph signal processing/ graph deep learning.) My eventual goal is research scientist at big tech, or whichever company
arXiv:2609.12899v1 Announce Type: new Abstract: Full waveform inversion (FWI) estimates subsurface velocity from seismic recordings, but its ill-posedness and nonlinearity make accurate reconstruction
arXiv:2609.12735v1 Announce Type: cross Abstract: High-frequency ultrasound (HFUS) enables noninvasive visualization of superficial skin structures, but automated skin-layer analysis is limited by the
arXiv:2609.11935v1 Announce Type: new Abstract: Neural operators such as the Fourier Neural Operator (FNO) achieve remarkable accuracy in approximating solutions to partial differential equations (PDE
arXiv:2609.12491v1 Announce Type: new Abstract: Skeleton-based action recognition can support automated tracking of physiotherapy exercises, particularly in remote rehabilitation settings where contin
arXiv:2609.13012v1 Announce Type: new Abstract: Vision-language models retain a substantial amount of pixel-decodable visual content in their visual key-value cache. We show, in our setting, that this
arXiv:2609.12225v1 Announce Type: cross Abstract: Out-of-Distribution (OOD) data poses a significant threat to machine learning models, often leading to model failure during deployment. All existing O
arXiv:2609.12258v1 Announce Type: new Abstract: Animals coordinate their movements through distributed neural circuits, but soft robots still typically depend on external, centralized electronics for
arXiv:2609.12132v1 Announce Type: new Abstract: Food access is multidimensional, but population-level measurement still relies heavily on geography because perceived dimensions of access are difficult
arXiv:2609.12223v1 Announce Type: new Abstract: Collision cross section (CCS), derived from ion mobility mass spectrometry, is a common descriptor for molecular annotation. Prediction is challenging f
arXiv:2609.12724v1 Announce Type: cross Abstract: sEMG is vulnerable to various contaminants that distort signal morphology and spectral content. Accurate signal quality assessment (SQA) is essential
arXiv:2609.11559v1 Announce Type: cross Abstract: Large language models (LLMs) and AI-enabled software increasingly participate in systematic-review decisions, yet the information needed to audit thes
arXiv:2609.12658v1 Announce Type: new Abstract: Streaming video understanding requires models to process continuous multimodal input while maintaining temporal context. Existing evaluations are predom
arXiv:2609.12614v1 Announce Type: new Abstract: A 3D scene graph groups objects into rooms. When a robot is asked to fetch an object from the kitchen, that grouping is what tells it where to look. An
arXiv:2609.12011v1 Announce Type: new Abstract: In small-scale binary sentiment classification scenarios, factors such as negation, contrastive shifts, and cross-word dependencies lead to the non-line
arXiv:2609.12122v1 Announce Type: new Abstract: Consonants contribute unequally to whether a word is understood. Given the limited time available for therapy, ranking consonants by contribution to int
arXiv:2609.12891v1 Announce Type: new Abstract: In practice, various learning scenarios provide access to auxiliary features exclusively during training. Incorporating such data to enhance model perfo
arXiv:2609.13040v1 Announce Type: new Abstract: We study loss-based filtering for finite-sum optimization with a subset of corrupted component functions whose gradients may be highly unreliable. Motiv
arXiv:2609.11955v1 Announce Type: new Abstract: Large language models are increasingly used for automated fact checking, but end-to-end prompting often entangles evidence retrieval, reasoning, and unc
arXiv:2609.12089v1 Announce Type: cross Abstract: Detecting whether a transmitter is actively communicating with a receiver is a fundamental problem in molecular communications. A spherical receiver m
arXiv:2609.12020v1 Announce Type: new Abstract: A key subtask of quantum error correction is to extract a syndrome that, if nontrivial, signals an error. The number of possible ways to extract a syndr
arXiv:2609.12261v1 Announce Type: new Abstract: Multi-object tracking (MOT) is dominated by the tracking-by-detection paradigm, whose methods typically rely on a small set of hyperparameters that are
arXiv:2609.12497v1 Announce Type: new Abstract: Infrared-visible image fusion facilitates robust multimodal perception by integrating complementary textural nuances from visible sensors with thermal s
arXiv:2609.12814v1 Announce Type: new Abstract: Linear attention and state-space models provide linear-time sequence modeling, but their recurrent memory remains a second-order tensor (a matrix), limi
arXiv:2609.12761v1 Announce Type: new Abstract: Vision encoders for Cell Painting are typically ranked by a single evaluation, commonly replicate mean average precision (mAP). We introduce CP-BG-Bench
arXiv:2609.12317v1 Announce Type: new Abstract: A central question in LLM reasoning is whether reinforcement learning (RL) instills genuinely new capabilities or merely reshapes how existing knowledge
arXiv:2609.12067v1 Announce Type: new Abstract: Channel simulation has recently emerged as a useful component in machine learning systems where samples from a prescribed probability distribution are t
arXiv:2609.12113v1 Announce Type: new Abstract: Outliers are important for stress-testing algorithms and understanding system behaviour under rare conditions. Despite being commonly described as low-l
arXiv:2609.12577v1 Announce Type: new Abstract: Lifelong Person Re-Identification (LReID) aims to train a unified person retrieval model from a non-stationary data stream. Existing LReID methods mainl
arXiv:2609.12834v1 Announce Type: new Abstract: Modelling how a disease progresses over time requires longitudinal imaging cohorts, which are scarce and small, whereas cross-sectional data -- one imag
arXiv:2609.12305v1 Announce Type: cross Abstract: The rapid growth of Distributed Energy Resources (DERs) has significantly expanded the cyber attack surface of modern power grids. Furthermore, increa
arXiv:2609.12690v1 Announce Type: new Abstract: Continuous and cuffless blood pressure (BP) monitoring using photoplethysmography (PPG) is of great interest for low-cost and personalized cardiovascula
arXiv:2601.08514v3 Announce Type: replace Abstract: This paper introduces a novel modular architecture for ROS2 that decouples the logic required to acquire, validate, and interpolate references from
arXiv:2609.12599v1 Announce Type: new Abstract: Multi-task learning (MTL) requires navigating unavoidable trade-offs among competing objectives. This paradigm is frequently formulated as multi-objecti
arXiv:2609.12155v1 Announce Type: new Abstract: Understanding person-level bi-manual interactions requires not only detecting hands, but also identifying which two hands belong to the same person and
arXiv:2609.12417v1 Announce Type: new Abstract: Multiview point cloud registration is particularly challenging in low-overlap scenes, where reliable correspondences are limited and incorrect pairwise
arXiv:2609.12386v1 Announce Type: new Abstract: Conformal prediction provides distribution-free uncertainty quantification under exchangeability. However, this assumption is violated by label shift, w
arXiv:2503.00612v2 Announce Type: replace-cross Abstract: The basic problem of semantic compression is to minimize the length of a message while preserving its meaning. This differs from classical not
arXiv:2508.11450v2 Announce Type: replace-cross Abstract: Subcortical segmentation in neuroimages plays an important role in understanding brain anatomy and facilitating computer-aided diagnosis of tr
arXiv:2609.12997v1 Announce Type: new Abstract: Single Ventricle Physiology (SVP) is a rare subtype of congenital heart disease characterized by the presence of a single functional cardiac ventricle w
arXiv:2609.12531v1 Announce Type: new Abstract: In streaming tasks, recurrent models can carry latent computation across time, allowing each update to build on representations produced earlier. This r
This story appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. This weekend, Dario Amodei, CEO of Anthropic, posted an essay calling for