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Computer Vision
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The newest 5,000 papers, from 29 September 2026 to 5 November 2026: 4,999 arXiv preprints and 1 OpenAlex record.
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Newest papers, page 191
Adversarially Trained Linear Transformers Are Optimal Robust In-Context Learners for Gaussian Mixtures
Adversarial training is one of the most reliable defenses against adversarial attacks, but its high computational cost must generally be paid anew for each task.Later Is Better: Token Reduction for ViTs Under Distribution Shift
Training-free token reduction accelerates vision transformers by removing redundant tokens across layers, recovering most of the original accuracy at a fraction of the compute.From Laboratory to Road: Evaluating Wearable Gaze Accuracy for Driving
Bird's-eye-view (BEV) representations have become a widely used interface between perception and planning in autonomous driving, but they encode what is in a scene, not what is behaviorally relevant…Image-Space Refraction Correction for Underwater 3D Reconstruction: Warping Flat-Port Views into Pinhole Perspective
Consumer-grade cameras in flat-port housings are widely used for underwater exploration and mapping of coral reefs and seafloor habitats due to their low cost and accessibility.Geometry-Constrained Bidirectional Point Cloud Registration for Thin, Sheet-Like Heritage Artifacts
Non-contact three-dimensional reconstruction of thin, sheet-like heritage artifacts poses significant geometric and registration challenges.Efficient Gaussian Splatting Sequence Compression with Standard Video Codecs
This paper presents a novel effective Gaussian Splatting (GS) sequence Compression method that utilizes the Video codec (GSCV).Towards benchmarking Western Bluebird detection in the wild
Bird monitoring in natural environments is challenging due to the small size of some species of birds relative to the scene, background clutter, variability in illumination, and the observers'…$α$Transfer: Coefficient Transfer for Efficient Model Merging
Model merging offers a promising solution for combining multiple fine-tuned checkpoints into a single model through parameter arithmetic.CHARTER: Auditing Reference Substitution in Hierarchical Compact-Evidence Evaluation for Computational Pathology
In digital pathology, compact evidence is often used to explain or audit predictions made by whole-slide image multiple instance learning models.CueRator: Agentic Search for Symbolic Rules to Adapt Frozen Multimodal Encoders
Large language model agents have been used to search over symbolic structures such as programs and equations.Revar3r: gauge-aware perturbation uncertainty for feed-forward 3d reconstruction
A correctly reconstructed distant point appears uncertain even when a frozen 3D model processes equivalent inputs because its output frame rotates fractionally.Label-Efficient Deep Learning for ECG Delineation: A Multi-Dataset Benchmark against Widely Used Delineation Tools
Electrocardiogram (ECG) delineation, the identification of waveform boundaries, is a foundational step that translates raw ECG signals into clinically interpretable measurements.Visual Abstention in Unified Multimodal Models
Unified multimodal models (UMMs) integrate understanding and generation, yet their generative behavior is rarely governed by what they understand about the task.Unsupervised Long-Tailed Adaptation of Vision-Language Models
Adapting vision-language models to downstream tasks has achieved remarkable success by leveraging pseudo-labels generated from unlabeled data.Diverse Motion Customization via Control-based Dynamic Optimization
Despite recent advances in video generation, motion customization remains challenging due to content leakage, where appearance attributes from the reference video unintentionally propagate into the…Multimodal Knowledge Distillation for Gastric Adenocarcinoma Classification from Whole-Slide Images
Gastric adenocarcinoma (GA) is a leading cause of cancer-related mortality worldwide, and accurate histopathological subtype classification from whole-slide images (WSIs) is essential for effective…Can We Model the Artifacts Explicitly? Disentangle Artifacts via Pairwise Edit Relations for Image Manipulation Localization
Image Manipulation Localization (IML) is commonly formulated as a fully supervised learning task that estimates the optimal manipulation mask $y$ for a given image $x$.OpenWAM: An Open Framework for Composable World-Action Models
World-action models (WAMs) couple future prediction with robot control, yet existing systems often vary the video backbone, interaction structure, supervision, and inference procedure…TF-PRVR: Training-Free Partially Relevant Video Retrieval
Partially Relevant Video Retrieval (PRVR) aims to retrieve untrimmed videos containing moments relevant to a given text query.Dynamic Alignment and Calibration for Multimodal Learning
Dynamic multimodal learning aims to learn robust representations by adaptively modeling information discrepancies across modalities.