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Guided Super-Resolution of Digital Elevation Models with Diffusion-Based Image Generators

arXiv:2609.11886v1 Announce Type: new Abstract: High-resolution digital surface models (DSMs) play an important role in urban analysis, 3D building reconstruction, and infrastructure monitoring, yet t

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Hierarchical Clustering Can Jointly Satisfy Richness, Consistency, and Scale Invariance

DGX agent

arXiv:2609.11173v1 Announce Type: new Abstract: Despite its ubiquity, clustering lacks a universally accepted definition of what is a cluster. Kleinberg's Impossibility Theorem formalizes this difficu

researcharxiv-cs-lg

11 Sept 2026

How Wrong Can a Good Predictor Be? Diverging Updates with Vanishing Predictive KL

arXiv:2609.11132v1 Announce Type: new Abstract: Accurate posterior prediction need not require accurate approximation of Bayesian updates. We prove that an unbounded gap between the update maps can co

Identifiability of Nonnegative Tensor Decompositions via Positive Scattering

arXiv:2609.11606v1 Announce Type: cross Abstract: Identifiability of tensor decompositions is often established through linear-algebraic conditions on the factor families. For nonnegative decompositio

InstantHDR: Single-forward Gaussian Splatting Initialization for HDR 3D Reconstruction

arXiv:2603.11298v3 Announce Type: replace Abstract: High dynamic range (HDR) novel view synthesis (NVS) aims to reconstruct HDR scenes from multi-exposure low dynamic range (LDR) images. Existing HDR

Learning Intrusion Response Strategies for OT Systems

arXiv:2609.10298v1 Announce Type: cross Abstract: Cyberattacks against Operational Technology (OT) systems, which monitor and control industrial processes, pose an increasing threat to essential socie

researcharxiv-cs-ai

Learnware and AI Model Management System

arXiv:2609.11656v1 Announce Type: new Abstract: The transition from file storage to database management systems transformed stored data into managed resources. AI now faces an analogous transition fro

Legible Failures: Detecting and Repairing In-Context Binding Errors

arXiv:2609.11216v1 Announce Type: new Abstract: A wrong answer does not show whether the model lacked the needed information or held it and failed to use it. On an entity-obligation binding task, a la

Leveraging LLMs for Context-Aware Implicit Textual and Multimodal Hate Speech Detection

arXiv:2510.15685v2 Announce Type: replace Abstract: This paper investigates the use of an LLM to generate auxiliary background context for social media posts, and explores four methods to incorporate

Lie-Algebraic Bell Recurrences for Arbitrary-Order Twist Jets and Parallel-Mechanism Closure

arXiv:2609.10748v1 Announce Type: new Abstract: This paper develops an arbitrary-order kinematic construction that links serial propagation, parallel-mechanism closure, and rigid-platform point fields

LoaDiff: Conditional Generation of Electricity Consumption Time Series for Energy Analytics

arXiv:2609.11639v1 Announce Type: new Abstract: The energy transition is reshaping residential electricity consumption through the increasing adoption of distributed generation, electrified appliances

Longitudinal Risk Prediction in Mammography with Privileged History Distillation

arXiv:2603.15814v2 Announce Type: replace Abstract: Longitudinal mammography screening has become an important source of information for improving future breast cancer risk prediction. However, the pe

Mapping Seven Decades of Philosophy in Colombia: Dynamic Topic Modelling of Ideas y Valores

arXiv:2412.04236v2 Announce Type: replace-cross Abstract: Data-driven approaches to philosophy have emerged as a valuable tool for studying the history of the discipline. However, most studies in this

Measuring the Value of World-Model Updates: A Counterfactual Utility Protocol for Continual Adaptation

arXiv:2609.10954v1 Announce Type: new Abstract: Continual world models must decide whether new data justify changing the model. Fixed replay schedules and prediction-error triggers specify when to upd

Meta-Learning for Classifier Selection in Image Datasets: A Feature-Driven Framework for Accuracy Prediction

arXiv:2609.11041v1 Announce Type: new Abstract: No Free Lunch theorem implies that any performance gains achieved by a classifier on a particular image distribution are necessarily offset by a loss of

Meta-Learning for Data-Efficient Plant Growth Estimation via Vision Transformers and Fuzzy Clustering

arXiv:2609.10749v1 Announce Type: new Abstract: Accurate plant growth estimation is essential for greenhouse monitoring, yet obtaining labeled data remains costly and time-consuming. To address this,

MHE-Former: Multi-Hypothesis Transformers via Entropy Maximization for 3D Mesh Recovery

arXiv:2609.10743v1 Announce Type: new Abstract: Monocular 3D hand and body mesh recovery often suffers from severe occlusion and ambiguity. Traditional deterministic methods typically regress a single

Mi-Ripple: Restoring Images Degraded by Iterative AI Editing

arXiv:2609.11317v1 Announce Type: new Abstract: Iterative reference-conditioned image editing can introduce grid-like and granular textures, commonly described as digital ripple. We present Mi-Ripple,

'Mirror' Large Language Model Evaluations of Depression are Criterion Contaminated

arXiv:2508.05830v3 Announce Type: replace Abstract: Large Language Model (LLM) studies that use language responses elicited from depression assessments to predict scores on those same assessments ofte

Model-Aware Schedules Improve Generation via Fiberwise Optimal Transport

arXiv:2609.11842v1 Announce Type: new Abstract: Diffusion and flow-matching schedules control the signal and noise coefficients that mix data and noise along affine probability paths. Minimizing a kin

Modular Kinematic Reduction of Closed-Chain Mechanisms Using Path Assembly and Defect Homotopy

arXiv:2609.11338v1 Announce Type: new Abstract: Closed kinematic chains complicate modular modeling by coupling active and passive coordinates through nonlinear closure constraints. This paper present

More than half of recent astronomy papers are written with language-model assistance

arXiv:2609.10664v1 Announce Type: cross Abstract: Language models leave a distinctive vocabulary in the prose they help write, and we measure how much of the astronomy literature now carries it. From

MUC-FL: Block-Wise Marginal Utility Contribution for Communication-Efficient Federated Learning

arXiv:2609.10545v1 Announce Type: cross Abstract: Federated Learning (FL) enables distributed model training without centralizing data but suffers from high communication overhead. To address this, we

MultiHuSE: A Multimodal Dataset for Humour Styles and Emotions

arXiv:2609.11322v1 Announce Type: new Abstract: Computational recognition of verbal humour remains a challenging task, requiring an understanding of language, delivery style, emotions, and cultural co

Musec: MomentUm SpEctral Clipping for Stable Muon-type Training

arXiv:2609.11655v1 Announce Type: new Abstract: Muon has emerged as a highly effective optimizer for large language model training, often achieving superior convergence and performance compared with t

No Screening is More Efficient with Multiple Objects

arXiv:2408.10077v4 Announce Type: replace-cross Abstract: We study the welfare-maximizing allocation of heterogeneous objects when screening uses costly effort rather than monetary transfers. No-scree

OmniKVQuant: KV Cache Quantization for Omni-LLMs

arXiv:2609.11582v1 Announce Type: new Abstract: As Omni-modal large language models (Omni-LLMs) take in audio, video and text together, their KV cache memory cost grows. KV cache quantization is the d

On the Impact of Anonymization on the Performance of Large Language Models

arXiv:2609.11335v1 Announce Type: new Abstract: As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has becom

On the Relation between Code Quality and Machine Learning Performance: A Large-scale Empirical Study

arXiv:2609.10610v1 Announce Type: cross Abstract: Context: Computational notebooks are the standard environment for machine learning (ML) development. Within the ML community, model performance is oft

Output Embedding Centering for Stable LLM Pretraining

arXiv:2601.02031v3 Announce Type: replace-cross Abstract: Pretraining of large language models is not only expensive but also prone to certain training instabilities. A specific instability that often

Overpainting: Localized Context-aware Diffusion Image Editing

arXiv:2609.10811v1 Announce Type: new Abstract: We present 'overpainting', an image editing operation which offers both control over the location of the edit and awareness of the previous content in t

Pairit: A Platform for Live Experiments on Human-AI Collaboration

arXiv:2609.09789v1 Announce Type: cross Abstract: Organizational design in the era of artificial intelligence requires experimental methods that can test how human-AI groups coordinate, delegate, and

researcharxiv-cs-ai

Partial GFlowNet: Accelerating Convergence in Large State Spaces via Strategic Partitioning

arXiv:2602.11498v2 Announce Type: replace Abstract: Generative Flow Networks (GFlowNets) have shown promising potential to generate high-scoring candidates with probability proportional to their rewar

Particle GFlowNets: Rethinking Generative Marginalization Models

arXiv:2609.11538v1 Announce Type: new Abstract: Generative Marginalization Models (MaMs) have been recently introduced as efficient neural sampling models for any-order autoregressive modelling of dis

PathoHR: Breast Cancer Survival Prediction on High-Resolution Pathological Images

arXiv:2503.17970v2 Announce Type: replace-cross Abstract: Breast cancer survival prediction in computational pathology presents a remarkable challenge due to tumor heterogeneity. For instance, differe

Periodic robust robotic rock chop via virtual model control

arXiv:2508.02604v4 Announce Type: replace Abstract: Robotic cutting is a challenging, contact-rich manipulation task where the robot must simultaneously negotiate unknown object mechanics, large conta

Perturbation: A simple and efficient adversarial tracer for representation learning in language models

arXiv:2603.23821v2 Announce Type: replace Abstract: Linguistic representation learning in deep neural language models (LMs) has been studied for decades, but finding representations in LMs remains an

PitchFlower: A flow-based neural audio codec with pitch controllability

arXiv:2510.25566v2 Announce Type: replace-cross Abstract: We present PitchFlower, a flow-based neural audio codec with explicit pitch controllability. Our approach promotes pitch disentanglement throu

Planning along Differentiable Charts of Constraint Manifolds with General-Purpose IK Solvers

arXiv:2609.10905v1 Announce Type: new Abstract: Planning trajectories for robot manipulators under kinematic equality constraints restricts feasible motions to a measure-zero submanifold of the config

Polyhedral Geometry of Time-to-First-Spike Neural Networks

arXiv:2609.11227v1 Announce Type: new Abstract: We study the expressivity of spiking neural networks, which provide a natural framework for asynchronous, event-driven computation complementary to conv

Predicting Privacy Leakage from Weight Spectral Density

arXiv:2609.11780v1 Announce Type: new Abstract: Membership inference attacks (MIAs) are widely used to audit the privacy disclosure risk of machine learning models, however current state-of-the-art at

Predicting Train Delays in Finland Using Machine Learning and Weather Data

arXiv:2609.11277v1 Announce Type: cross Abstract: Reliable railway operations depend increasingly on real-time environmental intelligence delivered through wireless sensor infrastructures, a capabilit

Predictive Multi-Landmark OCT Tracking for Increased Motion Robustness

arXiv:2609.11330v1 Announce Type: new Abstract: Optical coherence tomography is a promising modality for markerless motion tracking due to its high spatial resolution and inherent depth perception. Ho

Prevalence Determines Precision:Silent Contamination in Detector-Defined Datasets

arXiv:2609.11449v1 Announce Type: new Abstract: Many ML datasets are constructed by running a detector, heuristic, or model over candidate pools; accepted items become labels. Dataset precision is the

Processing and classifying bird songs using wavelet techniques and supervised learning

arXiv:2609.10826v1 Announce Type: new Abstract: This study proposes an integrated framework for the processing and classification of invasive bird species vocalizations within natural soundscapes, cha

Prototype Matters: Modality-unified Prototype Self-distillation for Unsupervised Visible-infrared Person Re-identification

arXiv:2609.11514v1 Announce Type: new Abstract: Estimating reliable cross-modality association is crucial to unsupervised visible-infrared person re-ID. While optimal transport is shown to be a practi

Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering

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Evaluating video captioning remains a critical challenge for Visual Large Language Models (VLLMs). Existing metrics primarily rely on matching generated text against ground-truth references. This para

Quantifying the Memorization-to-Generalization Transition: Scaling Laws and Phase Structure in Grokking

arXiv:2609.10657v1 Announce Type: cross Abstract: Neural networks trained past memorization frequently undergo a delayed transition to generalization, a phenomenon known as grokking. Despite theoretic