Search: “research”

Measurement-Gated Provenance Attenuation for Frozen EEG Representations

arXiv:2609.32889v1 Announce Type: new Abstract: Frozen EEG representations retain acquisition signatures as well as neural activity. Source predictability alone does not identify what should be remove

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Measuring the evolution of camera distance across a century of film

DGX agent

arXiv:2609.31734v1 Announce Type: new Abstract: The rise of computer vision and artificial intelligence has made possible new forms of large-scale computational measurement. We apply these techniques

researcharxiv-cs-cv

29 Sept 2026

Mechanistic Interpretability Reveals Shared Causal Subspaces in Brain-to-Speech Decoders

arXiv:2609.31992v1 Announce Type: new Abstract: Decoding covert speech, such as mimed or imagined, from brain activity is harder than decoding vocalized speech. Cross-modal transfer, where information

Mend the Measurement Gap: Latent User Preference Modeling for Short-Form Video Recommendation

arXiv:2609.32839v1 Announce Type: cross Abstract: Recommender systems rely heavily on heterogeneous behavioral feedback to infer user preference. Although abundant, these signals are imperfect measure

MeqMuon: Matrix-Equilibrating Muon for LLM Pretraining

arXiv:2609.35701v1 Announce Type: new Abstract: The success of large language models (LLMs) has been accompanied by continued growth in model size and pretraining costs. Muon offers high accuracy and

MiCo: Mutual Information Coverage Optimization through Semantic Erasure Modeling for Efficient MLLM Inference

arXiv:2609.34330v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated impressive performance in multimodal understanding, but processing large numbers of visual to

Mind the RefGAP: Correcting Reference Attention in Diffusion-Based Visual Editing

arXiv:2609.35708v1 Announce Type: new Abstract: Reference-guided diffusion editors struggle to faithfully reproduce user-provided references. We identify a potential bottleneck in diffusion editors: m

Minimax Last-Iterate Convergence in Matrix Games with Observed Actions

arXiv:2609.34656v1 Announce Type: new Abstract: We study last-iterate convergence in unknown two-player zero-sum matrix games with bandit payoff feedback and observed opponent actions. For games with

Mixed-Prior Decision Risk for Open-Set Recognition

arXiv:2609.35043v1 Announce Type: new Abstract: In open-set recognition (OSR), a probe must either be identified as one of the known gallery classes or rejected as unknown, so three error types coexis

Model-Agnostic Online Certificate-Driven Calibration for Time Series Forecasting Under Distribution Shift

arXiv:2609.31960v1 Announce Type: new Abstract: Time series out-of-distribution generalization requires forecasters to remain reliable when deployment dynamics differ from training conditions due to c

Modeling Whole-Slide Images as Dynamic Tumor Microenvironment Fields

arXiv:2609.34451v1 Announce Type: new Abstract: Due to the gigapixel-scale nature of whole-slide images (WSIs), weakly supervised WSI analysis is commonly formulated as a multiple instance learning (M

Modernising the Compressed-Domain Video Captioner: A Controlled Study of SigLIP2 and GPT-2 Substitutions

arXiv:2609.31700v1 Announce Type: new Abstract: Compressed-domain video captioning avoids full video decoding by operating directly on I-frames, motion vectors and residuals, trading a small amount of

MoGround: Measuring and Mitigating Modality Distraction in Vision-Language Models

arXiv:2609.33431v1 Announce Type: new Abstract: We release MoGround, a vision-language dataset spanning four visual domains in which the answer to every question is guaranteed to be available from exa

MoSPR: Histology-to-Gene Expression Prediction with Morpho-Spatial Macrostates and Low-Rank Molecular Programs

arXiv:2609.34280v1 Announce Type: cross Abstract: Predicting molecular profiles from histopathology remains challenging because whole-slide images contain spatially organized, heterogeneous tissue pat

MotionSpaceFlow: Representation-Aware Flow Matching in Direct Motion Space

arXiv:2609.34190v1 Announce Type: new Abstract: Recent advances in diffusion and flow models have substantially improved text-driven human motion generation. Yet most methods generate in low-dimension

Multi-Aperture PPG with MAPIS: Spatial Optical and Temporal Coherence Fields

arXiv:2609.33790v1 Announce Type: cross Abstract: Conventional reflectance photoplethysmography (PPG) typically reduces tissue optical responses to one or a few detector channels. Matrix Pinhole Image

Multi-Attractor GNNs: Set-Valued Expressivity Beyond Unique Equilibria

arXiv:2609.35274v1 Announce Type: new Abstract: Recurrent and equilibrium graph neural networks (GNNs) often enforce a unique fixed point or use one training target per graph. Yet many combinatorial a

Multi-Modal Non-Prehensile Estimation of Physical Parameters via Press-and-Pull Tipping

arXiv:2609.33138v1 Announce Type: new Abstract: Recovering physical properties of unknown objects through non-prehensile interaction is challenging because no single manipulation primitive reveals all

researcharxiv-cs-ro

MultiEcho: An Experimental Science of Learned Worlds

arXiv:2609.33347v1 Announce Type: new Abstract: World models can be studied as experimental systems with response laws of their own. We introduce MultiEcho, a framework for estimating these laws throu

Muon Under Gradient Noise and the Limits of Orthogonalization Near Optima

arXiv:2609.32861v1 Announce Type: new Abstract: Muon replaces the momentum buffer of each weight matrix by its orthogonal polar factor. We ask what this orthogonalization does near an optimum, where m

NavJev: Efficient Vision-Language Navigation via Action-Centric Visual Compression and Discriminative Action-Semantic Memory

arXiv:2609.34969v1 Announce Type: new Abstract: Recent zero-shot Vision-and-Language Navigation (VLN) methods increasingly rely on multimodal large language models (MLLMs) to reason over visual observ

researcharxiv-cs-ro

Neural Dynamics as the Composition of Quantized Units

arXiv:2609.32487v1 Announce Type: new Abstract: Deep learning is commonly interpreted at two levels: the macroscopic, through aggregate trends in loss summarized by scaling laws, and the microscopic,

Neural Network-Assisted Refinement of Traditional Schemes for One-Dimensional Scalar Conservation Laws

arXiv:2609.32887v1 Announce Type: cross Abstract: A clear link is established between conventional numerical methods and neural network approximations for solving one-dimensional scalar conservation l

Neural Scaling Laws of Transformer Operator Network

arXiv:2609.33533v1 Announce Type: cross Abstract: Transformers have emerged as powerful architectures for learning solution operators of physical systems. Empirically the prediction error has been obs

Neuron-Level Architecture Growth: A Controlled Evaluation for EEG Time-Series Decoding

arXiv:2609.33880v1 Announce Type: cross Abstract: Convolutional EEG decoders are trained at a fixed width, usually set by their authors on other data. Growing methods add neurons during training where

Noise-adapted Neural Operator for Robust Non-Line-of-Sight Imaging

arXiv:2508.09655v3 Announce Type: replace Abstract: This work has been submitted for possible publication. Copyright may be transferred without notice, after which this version may no longer be access

Non-Adaptive Learning of Sparse Erdos--Renyi Graphs via Affine Splitting

arXiv:2609.33704v1 Announce Type: cross Abstract: Graph learning from edge-detecting queries concerns the reconstruction of an unknown edge set on a known vertex set. Each query reports whether a spec

Notes on Generative Modeling for Feedback Control and Planning

arXiv:2609.33164v1 Announce Type: cross Abstract: In these notes, we view control as a dynamically constrained sampling problem on the state-space of a control system. With this viewpoint, we extend m

Nurnberg NLP at ChildSafeAds 2026: Structurally Dissimilar Voter Ensembles under Four Levels of Data Access

arXiv:2609.34986v1 Announce Type: cross Abstract: We describe the Nurnberg NLP system for ChildSafeAds 2026. The shared task asks what a monitoring system for commercial content in child-facing YouTub

NutriVision: Ingredient-Conditioned Fusion and Prediction for Single-Image Food Nutrition Estimation

arXiv:2609.33076v1 Announce Type: new Abstract: Nutrition estimation is a fundamental task in consumer diet tracking, clinical dietetics, chronic disease management, sports and hospital nutrition, and

On Temporal Binding in Large Audio Language Models

arXiv:2609.34806v1 Announce Type: cross Abstract: Reasoning about temporal structure of audio recordings requires Large Audio Language Models (LALMs) to associate sound events with their temporal posi

One Evaluation, Any Operating Point: Hypernetwork-Amortized MeanFlow for 3D MRI Reconstruction

arXiv:2609.31655v1 Announce Type: new Abstract: Generative priors reconstruct accelerated 3D MRI well but pay heavily at deployment: tens of network evaluations per volume, and protocol-specific hyper

One-Step Generative Modeling via Unbalanced Optimal Transport

arXiv:2609.32708v1 Announce Type: cross Abstract: Drifting models enable one-step generation by amortizing distribution transport into training, but this efficiency places greater demands on the trans

OneSign: Unifying Sign Language Understanding Tasks with One Model

arXiv:2609.33090v1 Announce Type: cross Abstract: SLU encompasses a diverse set of tasks, including ISLR, CSLR, and SLT. Although these tasks share basic semantic and linguistic foundations, they are

Optimizing and Securing the Modern Watermarking Channel for Images

arXiv:2609.34744v1 Announce Type: cross Abstract: To comply with recent regulations requiring traceable generated content, modern watermarking has adopted multi-bit post-hoc watermarking schemes. Thes

Oracle-Efficient Online Classification with Stochastic Inputs and Adversarial Outputs

arXiv:2609.33760v1 Announce Type: new Abstract: We consider contextual binary prediction with i.i.d. contexts from an unknown distribution and adaptively chosen losses. We show that a simple Follow-th

OrientedFormer: An End-to-End Transformer-Based Oriented Object Detector in Remote Sensing Images

arXiv:2409.19648v2 Announce Type: replace Abstract: Oriented object detection in remote sensing images is a challenging task due to objects being distributed in multi-orientation. Recently, end-to-end

Orthogonal Witness Control for Muon Optimization via Sigmoid Spectral Reshaping

arXiv:2609.33194v1 Announce Type: new Abstract: Matrix-valued optimizers such as Muon exploit the spectral structure of neural network updates through Newton--Schulz orthogonalization, but their near-

P2P: Cross-View Population Denoising for Unpaired Single-Cell Perturbation Response Prediction

arXiv:2609.34391v1 Announce Type: cross Abstract: AIVC (AI Virtual Cell) is a learned simulator of cellular behavior across conditions. Predicting how a cell population responds transcriptionally to a

P4Q: Co-designing Token Pruning and Quantization for Vision-Language Model Acceleration

arXiv:2609.34867v1 Announce Type: new Abstract: Vision language models have achieved strong performance across a wide range of multimodal applications, yet their substantial computational and memory c

PACER: Progressive Availability-Conditioned Evidence Routing for Radiology Report Generation under Incomplete Clinical Context

arXiv:2609.34487v1 Announce Type: new Abstract: Radiology report generation (RRG) increasingly incorporates heterogeneous clinical evidence, such as multi-view radiographs and previous reports, whose

PACGNet: Pyramidal Adaptive Cross-Gating Network for Multimodal Object Detection in Aerial Imagery

arXiv:2512.18291v3 Announce Type: replace Abstract: Object detection in aerial imagery is challenging because targets are often small, backgrounds are cluttered, and imaging conditions vary substantia

Panoptic Scene Program Diffusion Transformer

arXiv:2609.31780v1 Announce Type: new Abstract: Modern text-to-image models produce high-fidelity images but still struggle with compositional prompts that require instance identity, attribute ownersh

Patch Rebirth: Toward Fast and Transferable Model Inversion of Vision Transformers

arXiv:2509.23235v2 Announce Type: replace Abstract: Model inversion is a widely adopted technique in data-free learning that reconstructs synthetic inputs from a pretrained model through iterative opt

Patient-level validation of a foundation-model pipeline for pediatric lung sounds: physician-annotated adventitious events are recognized, disease groups are not reliably predicted

arXiv:2603.15688v2 Announce Type: replace-cross Abstract: Background: Lung-sound classifiers are usually evaluated on recording- or event-level splits, although each child contributes many recordings.

Pay for Hints, Not Answers: LLM Shepherding for Cost-Efficient Inference

arXiv:2601.22132v2 Announce Type: replace Abstract: Large Language Models (LLMs) deliver state-of-the-art performance on complex reasoning tasks, but their inference costs limit deployment at scale. S

PDMD: Projected Distribution Matching Distillation for Video Diffusion Models

arXiv:2609.35768v1 Announce Type: new Abstract: Modern video diffusion models require tens of denoising evaluations over long spatiotemporal token sequences. Distribution Matching Distillation (DMD) r

PEEL-DDPM: Physics-Enabled Evidential Learning for the Denoising Diffusion Probabilistic Model

arXiv:2609.31742v1 Announce Type: new Abstract: Normal-inverse-gamma (NIG) regression is not identifiable from its marginal Student-t likelihood: three combinations of four NIG parameters are determin