Search: “research”

Forecast-Necessary Causal Discovery for Nonlinear Political Panel Data: Feedback, Functional Form, and the Dynamics of Democratization

arXiv:2609.34115v1 Announce Type: cross Abstract: A non-significant coefficient in a dynamic panel model need not imply the absence of a relationship. It may instead reflect heterogeneous effects aver

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ForeFly: A Dual-Horizon World Action Model for Aerial Vision-Language Navigation

DGX agent

arXiv:2609.33581v1 Announce Type: new Abstract: Aerial Vision-Language Navigation (AVLN) requires UAVs to maintain reliable instruction following over long trajectories in complex 3D environments. How

researcharxiv-cs-cv

29 Sept 2026

ForensicZoom: Adaptive Visual Inspection with Multimodal LLMs for Industrial-Grade Face Forgery Detection

arXiv:2609.31661v1 Announce Type: new Abstract: Reliable face forgery detection is critical to the security of online identity verification systems, where missed attacks compromise security and excess

Frequency-Domain AI-Generated Image Detection: Exploring Decoder and Channel Attention for Feature Refinement

arXiv:2609.31723v1 Announce Type: new Abstract: With the rapid progress of AI, the number of AI-generated images has increased significantly in recent years. However, the increasing variety of image g

From Distributions to Stochastic Processes: Neural Approximation of Measure-Valued Maps

arXiv:2609.33649v1 Announce Type: new Abstract: Learning mappings between probability distributions arises naturally when inputs and outputs are represented by populations of samples rather than indiv

From Feed-Forward to Flow: Unifying Reconstruction and Generation Is Easier Than You Think

arXiv:2609.32761v1 Announce Type: new Abstract: Reconstruct where the images provide evidence, and generate where they do not: recent success of spatial world models such as Atlas (World Labs Team, 20

From Grey-Box to Green-Box: When can Physics-Informed Machine Learning Reduce Carbon Footprints in Structural Health Monitoring?

arXiv:2609.33387v1 Announce Type: new Abstract: Machine learning plays an increasingly vital role in engineering, but the corresponding increase in compute time is not without environmental cost. Phys

From Language to Task Maps: Compiling Semantic Relations While Preserving Task-Relevant Freedom

arXiv:2609.34412v1 Announce Type: new Abstract: Natural-language manipulation instructions specify qualitative relations, whereas continuous controllers require state-evaluable task quantities, differ

From PDF to Evidence: Structure-Aware Retrieval for Clinical Practice Guidelines

arXiv:2609.33447v1 Announce Type: cross Abstract: Guideline documents are published as unstructured PDFs whose evidence is locked in visual structures---tables, flowcharts, and graded recommendations-

From Perception to Integration: Revisiting the Internal Dynamics of Reasoning in Vision-Language Models

arXiv:2609.34809v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer simple visual questions, but often struggle when one question requires several visual judgments. We study this

From Pixel Generation to Topological Inference: Structural Dual Super-Resolution for Trustworthy Cross-Physical-Domain Trabecular Morphology Learning

arXiv:2609.34716v1 Announce Type: new Abstract: Clinical CT and UHRCT cannot resolve individual trabeculae, whereas synchrotron radiation microCT (SR{mu}CT) provides 3.2{mu}m high-resolution reference

From Soft Targets to Reward Signals: How Assignment and Reward Objectives Interact

arXiv:2609.34850v1 Announce Type: cross Abstract: Soft preference targets specify supervision strength, and reward objectives convert that strength into learned reward signals. A central design questi

From UNI2-h to ConvNeXt-T: Lightweight Nuclei Instance Segmentation via Knowledge Distillation

arXiv:2609.35203v1 Announce Type: new Abstract: Nuclei instance segmentation is a core task in digital pathology, yet high-accuracy models rely on large vision transformer (ViT) encoders whose inferen

GAUGE: Planner-Conditioned Active Calibration of Opaque Quadruped Velocity Interfaces

arXiv:2609.32154v1 Announce Type: new Abstract: In this paper, we present a Goal-Aware Uncertainty-Guided Exploration (GAUGE) framework for planner-conditioned active calibration of opaque quadruped v

Gaussian Neural Networks

arXiv:2609.34825v1 Announce Type: new Abstract: Gaussian neural networks (GaNNs) are proposed as a novel regularization mechanism for neural networks. From a Bayesian perspective standard regularizati

Generalization Analysis of Online Stochastic Gradient Descent for Overparameterized Two-Layer Neural Networks

arXiv:2407.07670v2 Announce Type: replace-cross Abstract: We investigate the generalization performance of online stochastic gradient descent (SGD) for overparameterized two-layer neural networks unde

Generative Classifier for Domain Generalization

arXiv:2504.02272v2 Announce Type: replace Abstract: Domain generalization (DG) aims to improve the generalizability of computer vision models toward distribution shifts. The mainstream DG methods pred

Generative Residual Factorization

arXiv:2609.34824v1 Announce Type: new Abstract: Under a shared-factor model, the conditional law of the next image patch factors into a posterior over the shared scene factor and a residual kernel giv

GenNVS: Geometry-enhanced Novel View Synthesis via Disentangled 3D Prior

arXiv:2609.34579v1 Announce Type: new Abstract: Single-image novel view synthesis remains challenging because the underlying 3D geometry is highly ambiguous. Recent diffusion-based approaches produce

GeoCR: Learning a Generalist Cloud Removal Prior from Heterogeneous Observations

arXiv:2609.32510v1 Announce Type: new Abstract: Cloud removal methods are typically specialized to individual datasets and input configurations, limiting reuse across sensors, spectral bands, and obse

GeoGAE: Scalable Graph-Level Autoencoding via Hyperball Cloud Representations

arXiv:2609.35527v1 Announce Type: new Abstract: Embedding structured objects into Euclidean spaces has enabled a wide range of successful machine learning applications. Such objects include words, doc

Geometric Encoding for Spatial Reasoning in Vision-Language Models

arXiv:2609.34148v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are far more reliable at recognizing what appears in a video than at reasoning about its spatial and temporal properties,

Geometric Identification in Predict-Then-Optimize Learning

arXiv:2609.33472v1 Announce Type: new Abstract: Decision-focused surrogates can recover downstream decisions without identifying the quotient report. We characterize the equality set of the convex Sma

Geometry-Adaptive Mechanisms for Private Synthetic Data

arXiv:2609.33363v1 Announce Type: cross Abstract: Generating differentially private synthetic data with meaningful Wasserstein utility guarantees is challenging in high dimensions. For datasets of siz

Geometry as Address: Routing Attention to Visual Memory for Long-Horizon Camera-Controlled Video Generation

arXiv:2609.34722v1 Announce Type: new Abstract: Long-horizon camera-controlled video generation requires recovering previously observed content from an ever-growing visual history. Existing approaches

GeoShrink: Accelerating Diffusion Transformers with Two Lines of Code

arXiv:2609.33723v1 Announce Type: new Abstract: Diffusion transformers incur substantial inference cost through repeated model evaluations along a sampling trajectory. We introduce GeoShrink, a traini

GeoVerse: World-Consistent Novel View Synthesis in Geometric Latent Space

arXiv:2609.35734v1 Announce Type: new Abstract: Novel view synthesis from sparse images must reconcile faithful reconstruction of observed regions with plausible completion of unseen content, while ma

GlowTact: Simple and Compact Vision-Based Tactile Sensing with High Sensitivity and Spatial Resolution

arXiv:2609.32471v1 Announce Type: new Abstract: Vision-based tactile sensors (VBTS) provide rich contact information for robotic manipulation, but existing designs can be hard to simplify and adapt to

Goal-Conditioned Supervised Learning for Multi-Objective Recommendation

arXiv:2412.08911v4 Announce Type: replace Abstract: Multi-objective learning endeavors to concurrently optimize multiple objectives using a single model, aiming to achieve high and balanced performanc

GPARA: Graph-Posterior-Aligned Refinement and Active Acquisition for Grounding Diffusion Priors

arXiv:2609.34172v1 Announce Type: new Abstract: Active grounding of a frozen diffusion prior requires jointly determining where new measurements should be taken and how they should be used to refine t

GradLev: Token-Parallel Test-Time Training Via Costate Prediction

arXiv:2609.34174v1 Announce Type: new Abstract: Test-time training (TTT) allows a model to improve its predictions at inference time by updating weights after every observed token. However, sequential

Graph-Based Simultaneous Path and Foothold Planning for Multi-Limbed Intra-Vehicular Robots in Space Stations

arXiv:2609.35000v1 Announce Type: new Abstract: Robot-aided operations in space stations are essential for reducing the workload of astronauts and improving the efficiency of on-orbit activities. Mult

GraphSelect for Budgeted Representation Selection in Multimodal Graph Inference

arXiv:2609.33561v1 Announce Type: new Abstract: Multimodal graph predictors combine text, images, and relations to classify connected entities. How much of this input is needed to preserve their predi

Grounding Vision-Language Models in Driving Semantics: A Multi-Dataset Predicate Framework for Explainable Reasoning

arXiv:2609.31636v1 Announce Type: cross Abstract: Vision-language models are increasingly used for driving-scene understanding, yet the semantic relations expressed in their outputs are often difficul

Groupwise Selective State-Space Filtering for Accurate and Streaming Action Boundary Detection

arXiv:2609.33400v1 Announce Type: new Abstract: Action boundary detection partitions untrimmed video into intervals without assigning action classes. We present a boundary-detection adapter operating

HALO: Enhancing Time Series Generation via Hyperspherical Latents and Masked AutoregRessive Modeling

arXiv:2609.34511v1 Announce Type: new Abstract: Most existing time series generators rely on a two-stage modeling paradigm: the first stage learns discrete latent representations of time series; the s

Handwritten Digit Leakage from Smartphone Motion Sensors Across Unseen Users and Phone Models

arXiv:2609.32117v1 Announce Type: new Abstract: Smartphone motion sensors support interactive applications, but their readings may also reveal touchscreen input beyond their intended use. Assuming kno

Hard Vision, Easy Vision: What GPT-6 Astra Reveals Across Computer Vision

arXiv:2609.35718v1 Announce Type: new Abstract: Frontier general-purpose systems are rapidly expanding beyond visual understanding into capabilities traditionally handled by dedicated computer-vision

Harmonizing Spectral Evolution in Conditional Flow Matching for TTS

arXiv:2609.34431v1 Announce Type: new Abstract: Conditional Flow Matching (CFM) models for text-to-speech (TTS) suffer from incoherent frequency evolution during inference. While similar spectral imba

Harnessing Coupled Stream Completion For Human-Object Ineraction Modeling

arXiv:2609.32551v1 Announce Type: new Abstract: Text-conditioned human-object interaction (HOI) generation requires body motion, object trajectories & rotations, and hand articulation to remain coordi

Help Me Help You: The Aggregate Value of Source and Target Data in Transfer Learning

arXiv:2408.16189v3 Announce Type: replace-cross Abstract: Transfer learning, in regression or classification, concerns problems where one aims to use imperfect data from a source distribution P to imp

Hierarchical Frequency-Domain Compression of Implicit Geometric Representations for Large-Scale Point Clouds

arXiv:2609.32789v1 Announce Type: new Abstract: Large-scale point cloud representations of complex geome tries incur prohibitive computational and memory costs, necessitating compressed implicit repre

High-Probability Guarantees for SGD under eta-Heavy-Tailed Gradient Noise

arXiv:2609.32195v1 Announce Type: cross Abstract: Stochastic gradient descent (SGD) is widely used to train machine learning models, but subsampling the training data introduces noise into its updates

HOI-Retarget: Contact-Centric Retargeting for Human-Object Interaction

arXiv:2609.34674v1 Announce Type: new Abstract: Learning from demonstration (LfD) has enabled humanoid robots to acquire diverse whole-body skills, but extending this paradigm to human-object interact

How Linear Attention Remembers

arXiv:2609.33093v1 Announce Type: new Abstract: Linear attention replaces the growing key--value (KV) cache of standard attention with a fixed-size recurrent state, substantially reducing memory growt

HRIR-Former: Grid-Free Time-Domain Reconstruction of Head-Related Impulse Responses with a Spatially Encoded Transformer

arXiv:2603.27998v3 Announce Type: replace-cross Abstract: Individualized head-related impulse responses (HRIRs) enable binaural rendering, but dense per-listener measurements are costly. We address HR

HUMAN-TCI: Hierarchical Multi-Stream Motion-Aware Network with Torso-Centered Interaction for Text-to-Motion Retrieval

arXiv:2609.34430v1 Announce Type: new Abstract: Accurate retrieval of human motions is a crucial first step in text-guided human motion modeling and synthesis, as it selects semantically relevant sequ

HyperDAM: Hyperspectral Distractor-Aware Memory with Amodal Expansion for SAM 3 Tracking

arXiv:2609.34396v1 Announce Type: new Abstract: Hyperspectral video provides material cues that can disambiguate targets with similar false-color appearance, yet foundation-model trackers update memor