Knowledge catalogue
arXiv:2609.28448v1 Announce Type: cross Abstract: We study the nonequilibrium dynamics of a minimal recurrent transformer with N normalized tokens, Q=K=I, and a negative value map V=-I. Similarity-bas
arXiv:2609.27358v1 Announce Type: new Abstract: Field robots must traverse varied terrain and obstacles while remaining robust to water, debris, vegetation, and physical contact. We present MARBLE, a
arXiv:2609.28473v1 Announce Type: new Abstract: Representation Autoencoders (RAEs) enable diffusion models to operate in the feature spaces of pretrained visual encoders. However, many off-the-shelf e
arXiv:2312.17295v2 Announce Type: replace-cross Abstract: With the rise of large language models (LLMs) and concerns about potential misuse, watermarks for generative LLMs have recently attracted much
arXiv:2609.28442v1 Announce Type: cross Abstract: Reordering a set of mathematical rules without changing its meaning should preserve the correct answer, but must a model's internal representations st
arXiv:2609.27423v1 Announce Type: new Abstract: Most computer-vision systems organize visual input toward a predefined interpretation, such as semantic categories, prompted regions, learned object-lik
arXiv:2609.27489v1 Announce Type: cross Abstract: This paper introduces Passing, an interactive audiovisual installation that generates an endless journey from a single continuous monorail-window reco
arXiv:2609.27633v1 Announce Type: new Abstract: High-throughput single-cell data is now collected across large patient cohorts. Understanding patient-level heterogeneity from cellular-level data motiv
arXiv:2609.27554v1 Announce Type: cross Abstract: Multimodal learning is emerging as a powerful paradigm for AI for Physics (AI4Physics), where predicting physical systems requires the joint interpret
arXiv:2609.27222v1 Announce Type: cross Abstract: Pneumonia is difficult to diagnose in older long-term care residents; multimorbidity and atypical presentations obscure signs, motivating operationall
arXiv:2609.28022v1 Announce Type: cross Abstract: Space weather early warning depends on detecting solar wind transients in in-situ measurements at the first Sun-Earth Lagrange point (L1), before they
arXiv:2609.27145v1 Announce Type: new Abstract: Robot navigation methods tend to avoid contact, and consequently search for collision-free trajectories. For robots with high inertia and limited maneuv
arXiv:2609.27094v1 Announce Type: cross Abstract: Automatic tagging is a core task in Music Information Retrieval (MIR), yet most tagging systems exploit only audio. Live music performance is inherent
arXiv:2609.28270v1 Announce Type: new Abstract: Weight-space post-training quantization (PTQ) must choose finite formats, granularities, quantizer families, transformations, and bits before the comple
arXiv:2609.28434v1 Announce Type: new Abstract: Adolescent Idiopathic Scoliosis is defined as a lateral curvature of the spine that develops during adolescence, without known cause. The condition can
arXiv:2609.27206v1 Announce Type: cross Abstract: Prediction with expert advice is a fundamental problem in online learning. When the time horizon T is known in advance, the minimax cumulative regret
arXiv:2609.28116v1 Announce Type: new Abstract: Fast surrogates for tokamak boundary-plasma simulation are typically deterministic regressors mapping a global operating point to a flattened vector of
arXiv:2609.27936v1 Announce Type: new Abstract: Detecting illicit cryptocurrency transactions is hampered by extreme class imbalance, adversarial obfuscation, and a scarcity of reliable labels. While
arXiv:2609.27355v1 Announce Type: cross Abstract: Unlearning ensures LLM compliance by removing the influence of private or copyrighted training data. However, since LLM models typically undergo post-
arXiv:2609.26855v1 Announce Type: cross Abstract: Relational Deep Learning (RDL) models multi-table databases as heterogeneous temporal graphs, and graph transformers currently achieve state-of-the-ar
arXiv:2609.27845v1 Announce Type: cross Abstract: The landscape of search has changed drastically with how people look for information online. Traditional search engines are being replaced by Generati
arXiv:2609.27195v1 Announce Type: cross Abstract: Non-speech interference can change a speech representation without causing comparable task loss. We test eight frozen encoders on four tasks, adding n
arXiv:2009.13987v3 Announce Type: replace Abstract: We introduce a class of random polytopes which simultaneously generalizes several known constructions. While being fairly general, these polytopes a
arXiv:2609.28081v1 Announce Type: cross Abstract: Conventional image registration algorithms are robust to domain shifts and achieve low errors, but they are slow and computationally expensive. Deep-l
arXiv:2602.23006v3 Announce Type: replace-cross Abstract: Simulating a Gaussian process requires sampling from a high-dimensional Gaussian distribution, which scales cubically with the number of sampl
arXiv:2609.27890v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) fre- quently generate text that is inconsistent with the input image. While object- and attribute-level hallu
arXiv:2609.27202v1 Announce Type: cross Abstract: The growing deployment of Internet of Things (IoT) devices has increased the need for privacy-preserving intrusion detection systems that operate dire
arXiv:2609.27913v1 Announce Type: new Abstract: We study the problem of aggregating opinions from multiple black-box experts in noisy, conflict-prone settings where expert reliability varies across in
arXiv:2609.28263v1 Announce Type: new Abstract: The growth of large language model (LLM) inference and search services increases the scale of online linear programming problems, motivating computation
arXiv:2602.16715v2 Announce Type: replace Abstract: We explore the potential of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Graph-based RAG (GraphRAG) for generating Design
arXiv:2609.27546v1 Announce Type: cross Abstract: Score-based diffusion models are increasingly considered in settings where the underlying data distribution may differ from the training distribution,
arXiv:2609.26951v1 Announce Type: cross Abstract: We introduce Rolling Conformal Prediction (rolling-CP), a distribution-free predictive inference method for the setting of sequential model training.
arXiv:2609.27958v1 Announce Type: new Abstract: Implicit neural representations (INRs) have emerged as a promising paradigm for video compression, providing compact neural representations with flexibl
arXiv:2601.13566v2 Announce Type: replace-cross Abstract: Can language models improve their accuracy without external supervision? Methods such as debate, bootstrap, and internal coherence maximizatio
arXiv:2609.27854v1 Announce Type: cross Abstract: Multi-source remote sensing image classification has attracted increasing attention due to the complementary spectral, structural, and geometric infor
arXiv:2609.28006v1 Announce Type: new Abstract: Decoder-only Transformer language models cache keys and values (KV) to reuse past computation during generation. Sharing KV across layers saves storage
arXiv:2609.27008v1 Announce Type: cross Abstract: We study the long-time behavior of Wasserstein gradient flows for interaction energies [ mathsf E[mu] = frac12iint_{Mimes M}K(x,y),mathrm dmu(x),mathr
arXiv:2609.27621v1 Announce Type: new Abstract: Physical modeling and inverse design require computation that can continue from reusable state. We introduce SHRAV, an architecture-independent computat
arXiv:2609.26820v1 Announce Type: cross Abstract: Physiological time series such as electrocardiograms (ECG) and electroencephalograms (EEG) exhibit complex temporal structure, substantial acquisition
arXiv:2609.26836v1 Announce Type: new Abstract: Agentic AI systems are increasingly adopting automated pipelines that integrate multiple tools. While prior research and benchmarks have studied about t
arXiv:2606.13295v3 Announce Type: replace-cross Abstract: In the era of Explainable Artificial Intelligence, there is a renewed focus on single trees for their ease of interpretation. This paper intro
arXiv:2609.27980v1 Announce Type: new Abstract: Pruning large pre-trained transformer-based ASR models such as OpenAI's Whisper has seen great adoption, as pruning the decoder led to significant end-t
arXiv:2505.05491v2 Announce Type: replace-cross Abstract: Traffic sign detection is a challenging visual signal processing task for advanced driver assistance, where small objects, scale variation, an
arXiv:2609.28013v1 Announce Type: cross Abstract: Machine-learned interatomic potentials (MLIPs) for solid-liquid interfaces in advanced materials applications, e.g., electrochemistry, catalysis and c
arXiv:2609.27290v1 Announce Type: new Abstract: Short-horizon forecasts of atmospheric temperature are needed to support climate-aware digital-twin systems, but such forecasts must be produced where t
arXiv:2609.26854v1 Announce Type: cross Abstract: Sound Scene Generation is about the automatic synthesis of artificial sound scenes. We introduce SsgCaps, a publicly available dataset of human-engine
arXiv:2410.11113v4 Announce Type: replace-cross Abstract: This paper develops theory for deep neural network (DNN) estimators under dependent data. To provide theory applicable to a variety of DNN-bas
arXiv:2609.27238v1 Announce Type: new Abstract: Oriented ship detection in very high resolution (VHR) remote sensing imagery remains challenging due to elongated hull geometry and dense target distrib
arXiv:2609.27131v1 Announce Type: new Abstract: Single-image super-resolution of Sun's photospheric magnetograms enables consistent analysis across heterogeneous space-based instruments and supports l
arXiv:2409.13568v3 Announce Type: replace Abstract: Accurate delineation of agricultural field boundaries is essential for effective crop monitoring and resource management. However, competing methodo
arXiv:2606.19329v2 Announce Type: replace-cross Abstract: We present a framework to cross-match sources from the Chandra Source Catalog (CSC v2.1) with optical sources from Gaia Data Release 3. Unlike
arXiv:2609.26811v1 Announce Type: new Abstract: Local learning trains each layer with its own auxiliary loss and no global backward pass, which makes layer updates structurally parallel. Two problems
arXiv:2609.27158v1 Announce Type: cross Abstract: To make claims about representations that generalize beyond a particular trained model, we need to specify when two representations should count as eq
arXiv:2609.28466v1 Announce Type: new Abstract: Advances in generative models have improved video fidelity, enabling long-horizon generation, interactive world modeling, and evolving visual environmen
arXiv:2609.27765v1 Announce Type: cross Abstract: In safe hypothesis testing with test supermartingales, Ville's inequality provides anytime-valid type-I error guarantees for every significance level
arXiv:2609.26978v1 Announce Type: cross Abstract: We study online inverse linear optimization with a fixed unknown linear utility: in each round, an environment presents a compact action set, the lear
arXiv:2609.27868v1 Announce Type: cross Abstract: Octree-based 3D Gaussian Splatting organizes anchors into multi-level hierarchies for level-of-detail rendering, but features at different levels are
arXiv:2609.26990v1 Announce Type: cross Abstract: Natural Visibility Graph (NVG)-based representations provide a promising approach for capturing structural patterns in sequential network traffic. How
arXiv:2609.27675v1 Announce Type: new Abstract: Understanding articulated objects is fundamental for robotic interaction, requiring accurate rigid-part discovery and the recovery of their kinematic re
arXiv:2609.27037v1 Announce Type: new Abstract: Wake word detection is a critical component of virtual assistants, serving as the gateway to seamless user interactions. This paper introduces a novel w