Every paper checked — nothing hidden

All papers

Every paper checked for brief #4 of 12–19 Oct 2026 — nothing is hidden. Brief papers first.

All17,313 In brief24 More (on-topic)3,333 Not relevant13,754 Not assessed87 Older352 Could not confirm93 Blogs with no paper266 All blogs284

Paper	Topic	Relevance
Why 3D Reconstruction Breaks Down on Under-Ice AUV Video, and How to Predict It Analyzes reconstruction failures on under-ice underwater vehicle video and introduces a tool to flag camera baseline errors. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on under-ice 3D reconstruction failures, not multimodal models.
Why 3D Reconstruction Breaks Down on Under-Ice AUV Video, and How to Predict It Analyzes reconstruction failures on under-ice underwater vehicle video and introduces a tool to flag camera baseline errors. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Analyzes underwater AUV 3D reconstruction failures rather than industrial manufacturing inspection.
GDBA-Net: A Gated Dual-Branch Adaptation of SAM2 for Robust Cross-Domain Nuclei Segmentation Adapts a frozen segmentation model using a dual-branch adapter to improve cell nuclei segmentation across varied histopathology domains. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on pathology image segmentation using SAM2 adaptation, not multimodal vision-language reasoning.
GDBA-Net: A Gated Dual-Branch Adaptation of SAM2 for Robust Cross-Domain Nuclei Segmentation Adapts a frozen segmentation model using a dual-branch adapter to improve cell nuclei segmentation across varied histopathology domains. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Deals with cross-domain pathology nuclei segmentation, not manufacturing defect detection.
Feasibility of a Patient-Specific Digital Twin for Ventriculoperitoneal Shunt Trajectory Planning Constructs a digital twin from computed tomography scans to plan accurate surgical trajectories for ventricular shunt insertion. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on CT surgical trajectory planning, not multimodal models.
Feasibility of a Patient-Specific Digital Twin for Ventriculoperitoneal Shunt Trajectory Planning Constructs a digital twin from computed tomography scans to plan accurate surgical trajectories for ventricular shunt insertion. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Addresses surgical planning digital twins for ventricular shunts, not industrial inspection.
VisualWorldBench: A Fine-Grained Multi-Task Benchmark for Evaluating Visual World Knowledge in MLLMs Introduces a hierarchical multi-task benchmark to evaluate fine-grained visual world knowledge in multimodal large language models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Introduces a broad visual world knowledge benchmark, not industrial inspection.
When Pairwise Preferences Cycle: A Reliability-Anchored Preference Walk for Video GRPO Addresses cyclic preference graphs in reinforcement learning for video generation models using an anchored preference walk. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Addresses preference optimization in video generation, not industrial visual inspection.
When Pairwise Preferences Cycle: A Reliability-Anchored Preference Walk for Video GRPO Addresses cyclic preference graphs in reinforcement learning for video generation models using an anchored preference walk. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on reinforcement learning preference aggregation for video generation, not multimodal models.
RTAformer: Relation-Transition-Aware Transformer for Video Scene Graph Generation Models entity persistence and relation transitions separately to improve video scene graph generation accuracy during dynamic scene changes. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on video scene graph relation generation, not multimodal vision-language models.
RTAformer: Relation-Transition-Aware Transformer for Video Scene Graph Generation Models entity persistence and relation transitions separately to improve video scene graph generation accuracy during dynamic scene changes. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Addresses video scene graph generation rather than industrial inspection or defect detection.
RepForcing: Representation-Space Initialization for Autoregressive Video Distillation Uses representation-space supervision to initialize autoregressive video distillation students for faster and clearer generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on distilling video diffusion models, not industrial inspection or defect detection.
RepForcing: Representation-Space Initialization for Autoregressive Video Distillation Uses representation-space supervision to initialize autoregressive video distillation students for faster and clearer generation. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Covers video diffusion generation distillation rather than multimodal reasoning.
StreamErase: Towards Ultra-Fast Streaming Video Erasing Transfers capabilities from text-to-video foundation models to a unidirectional streaming model for real-time video object removal. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on streaming video inpainting and object erasure, not industrial vision.
StreamErase: Towards Ultra-Fast Streaming Video Erasing Transfers capabilities from text-to-video foundation models to a unidirectional streaming model for real-time video object removal. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on generative video object removal, not multimodal language-vision reasoning.
Attention-Based Spatio-Temporal Approach for Fire and Smoke Detection Combines spatial and temporal transformer modules to detect smoke and fire from camera video feeds. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses solely on video-based smoke and fire detection, not multimodal models.
Dataset-Level Regularization for Joint-Embedding Self-Supervised Learning Introduces dataset-level regularization stored in memory to prevent representation collapse in self-supervised learning with small batch sizes. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on self-supervised joint embedding regularization, not industrial visual quality control.
Dataset-Level Regularization for Joint-Embedding Self-Supervised Learning Introduces dataset-level regularization stored in memory to prevent representation collapse in self-supervised learning with small batch sizes. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Addresses self-supervised vision representation learning rather than multimodal vision-language models.
OneLA: Learning Many Worlds from Latent Actions Learns continuous latent actions from video data using an orthogonal dictionary to build cross-domain world models. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Studies visual world models and latent action spaces, not multimodal vision-language reasoning.
OneLA: Learning Many Worlds from Latent Actions Learns continuous latent actions from video data using an orthogonal dictionary to build cross-domain world models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Covers latent action spaces for video world models, not industrial inspection.
Continual pretraining Prostate MRI ViT Encoder for task alignment Applies low-rank continual pretraining to vision transformers to improve task alignment in prostate magnetic resonance imaging segmentation. Peer-reviewed	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Analyzes task alignment in vision encoders, not safety, guardrails, or jailbreaks.
Continual pretraining Prostate MRI ViT Encoder for task alignment Applies low-rank continual pretraining to vision transformers to improve task alignment in prostate magnetic resonance imaging segmentation. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Investigates unimodal medical MRI encoder pretraining rather than multimodal models.
Continual pretraining Prostate MRI ViT Encoder for task alignment Applies low-rank continual pretraining to vision transformers to improve task alignment in prostate magnetic resonance imaging segmentation. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Deals with medical MRI pretraining and segmentation, not industrial defect detection.
Continual pretraining Prostate MRI ViT Encoder for task alignment Applies low-rank continual pretraining to vision transformers to improve task alignment in prostate magnetic resonance imaging segmentation. Peer-reviewed	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Focuses on representation alignment in medical ViTs rather than model compression or efficient serving.
Continual pretraining Prostate MRI ViT Encoder for task alignment Applies low-rank continual pretraining to vision transformers to improve task alignment in prostate magnetic resonance imaging segmentation. Peer-reviewed	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Studies vision encoder task alignment rather than LLM benchmarks or evaluation methods.
Glance Forcing: Making Bidirectional Diffusion Autoregressive at a Glance Distills bidirectional video diffusion models into causal autoregressive models using an efficient single-sample supervision strategy. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Addresses video diffusion distillation rather than industrial vision or inspection.
Glance Forcing: Making Bidirectional Diffusion Autoregressive at a Glance Distills bidirectional video diffusion models into causal autoregressive models using an efficient single-sample supervision strategy. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on generative video diffusion distillation rather than multimodal language-vision models.
Contrastive uncertainty learning for robust multi-structure segmentation in lower-pelvic MR Uses contrastive uncertainty learning during training to improve anatomical boundary segmentation in pelvic magnetic resonance imaging. Peer-reviewed	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Studies segmentation uncertainty representations rather than efficient model inference or compression.
Contrastive uncertainty learning for robust multi-structure segmentation in lower-pelvic MR Uses contrastive uncertainty learning during training to improve anatomical boundary segmentation in pelvic magnetic resonance imaging. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Addresses unimodal 3D MRI medical segmentation rather than multimodal models.
Contrastive uncertainty learning for robust multi-structure segmentation in lower-pelvic MR Uses contrastive uncertainty learning during training to improve anatomical boundary segmentation in pelvic magnetic resonance imaging. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on clinical pelvic MRI segmentation rather than industrial manufacturing inspection.
Contrastive uncertainty learning for robust multi-structure segmentation in lower-pelvic MR Uses contrastive uncertainty learning during training to improve anatomical boundary segmentation in pelvic magnetic resonance imaging. Peer-reviewed	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Deals with boundary uncertainty in medical segmentation rather than AI safety or deployment guardrails.
Contrastive uncertainty learning for robust multi-structure segmentation in lower-pelvic MR Uses contrastive uncertainty learning during training to improve anatomical boundary segmentation in pelvic magnetic resonance imaging. Peer-reviewed	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Covers medical image segmentation loss, not LLM benchmark evaluation.
GLoD-LVSM: Learning Geometry-Grounded Continuous-LoD Scene Representations for Large View Synthesis Models Introduces a geometry-grounded scene representation with continuous levels of detail to compress large view synthesis models. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Addresses novel view synthesis and 3D scenes, not multimodal vision-language reasoning.
GLoD-LVSM: Learning Geometry-Grounded Continuous-LoD Scene Representations for Large View Synthesis Models Introduces a geometry-grounded scene representation with continuous levels of detail to compress large view synthesis models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on 3D view synthesis representation, not industrial vision or defect detection.
Resolution Allocation with Learnable Resizing and Spectral Filter Parameterization Investigates the interaction between learnable image resizing and spectral-domain convolutional filter parameterization in neural networks. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on unimodal vision convolutional filters rather than multimodal models.
Resolution Allocation with Learnable Resizing and Spectral Filter Parameterization Investigates the interaction between learnable image resizing and spectral-domain convolutional filter parameterization in neural networks. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Studies convolutional kernel parameterization rather than LLM evaluation or benchmark methodology.
Resolution Allocation with Learnable Resizing and Spectral Filter Parameterization Investigates the interaction between learnable image resizing and spectral-domain convolutional filter parameterization in neural networks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on CNN architecture filter properties rather than deployment safety, guardrails, or jailbreaks.
Resolution Allocation with Learnable Resizing and Spectral Filter Parameterization Investigates the interaction between learnable image resizing and spectral-domain convolutional filter parameterization in neural networks. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Investigates generic CNN downsampling and spectral kernels, not industrial defect detection.
Resolution Allocation with Learnable Resizing and Spectral Filter Parameterization Investigates the interaction between learnable image resizing and spectral-domain convolutional filter parameterization in neural networks. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Analyzes image classification filters rather than model compression, quantization, or efficient serving.
A Valid Watermark Is Not a Valid Identity: Spatial-Spectral Adversarial Face Evasion with Watermark Preservation Presents an adversarial evasion attack that fools face recognition systems while preserving embedded watermarks. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Examines biometric adversarial attacks on face recognition, not multimodal models.
A Valid Watermark Is Not a Valid Identity: Spatial-Spectral Adversarial Face Evasion with Watermark Preservation Presents an adversarial evasion attack that fools face recognition systems while preserving embedded watermarks. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Investigates facial recognition watermarking attacks rather than industrial vision or manufacturing quality control.
Event Cameras versus Frame Cameras for Synthetic-Aperture Imaging: A Simulation Study Compares event and conventional frame cameras via simulations for synthetic-aperture imaging through occluding scenes like foliage. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on airborne synthetic-aperture imaging simulations rather than industrial inspection or defect detection.
Event Cameras versus Frame Cameras for Synthetic-Aperture Imaging: A Simulation Study Compares event and conventional frame cameras via simulations for synthetic-aperture imaging through occluding scenes like foliage. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Deals with event camera optical integration rather than multimodal vision-language models.
InfiniSplat v2: Analyzing and Improving Feed-Forward 3DGS from Any Views Decouples geometry and appearance learning in Gaussian reconstruction to improve three-dimensional scene rendering across diverse views. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on 3D novel view synthesis, not multimodal cross-modal modeling.
InfiniSplat v2: Analyzing and Improving Feed-Forward 3DGS from Any Views Decouples geometry and appearance learning in Gaussian reconstruction to improve three-dimensional scene rendering across diverse views. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Novel view 3D Gaussian reconstruction, not industrial visual inspection.
ReferFlow: Beyond Final-Target Localization for Complex Referring Expressions This paper introduces ReferFlow-Bench and an accompanying method to evaluate and perform multi-step trajectory-level referring expression comprehension. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Referring expression comprehension, not industrial defect detection.
Look Before You Restore: Learning to Predict Before Acting for Agentic Image Restoration This paper proposes PreActIR, an agentic image restoration framework that forecasts tool consequences using a world model before taking action. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Agentic natural image restoration, not industrial manufacturing inspection.
STP-GUI: Spatially-Aware Token Pruning for Efficient Web-GUI Agents This paper introduces STP-GUI, a spatially aware token-pruning framework that preserves local interface structures for efficient web-GUI vision-language agents. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Web GUI screenshot processing, not industrial visual inspection.
Where Should the Gaussians Go? Reusable Label-Aware Allocation for Budget-Constrained Gaussian Splatting of Cinematic CT This paper proposes a reusable, label-aware front end to allocate fixed budgets of 3D Gaussians for cinematic CT visualization without per-case optimization. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Deals with CT rendering techniques, not multimodal vision-language understanding.
Where Should the Gaussians Go? Reusable Label-Aware Allocation for Budget-Constrained Gaussian Splatting of Cinematic CT This paper proposes a reusable, label-aware front end to allocate fixed budgets of 3D Gaussians for cinematic CT visualization without per-case optimization. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Medical CT scan 3D Gaussian splatting, not industrial inspection.
Hybrid supervised instance segmentation by learning label noise suppression This paper presents a hybrid instance segmentation pipeline that trains ancillary models to suppress label noise when combining bounding boxes with pixel masks. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Instance segmentation on standard benchmark datasets, not industrial defects.
Hybrid supervised instance segmentation by learning label noise suppression This paper presents a hybrid instance segmentation pipeline that trains ancillary models to suppress label noise when combining bounding boxes with pixel masks. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses strictly on unimodal computer vision instance segmentation.
Infant Fingerprints: Quality Assessment & Recognition This paper assesses ten fingerprint quality assessment methods on longitudinal infant data and proposes parameter tuning routines to improve recognition. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Biometric image processing, not multimodal reasoning across multiple modalities.
Infant Fingerprints: Quality Assessment & Recognition This paper assesses ten fingerprint quality assessment methods on longitudinal infant data and proposes parameter tuning routines to improve recognition. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Biometric infant fingerprinting, not industrial visual quality control.
OLiVES: An Outdoor Low-Light Video Benchmark for Enhancement and Segmentation This paper introduces OLiVES, a benchmark dataset of dynamic outdoor low-light videos designed for joint video enhancement and object segmentation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Outdoor low-light video enhancement, not industrial production inspection.
Generative Representation Learning for Scalable Latent Tokenization This paper develops a self-supervised representation learning approach based on pointwise mutual information factorisation for scalable generative latent tokenization. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Self-supervised generative tokenization, not industrial inspection.
Generative Representation Learning for Scalable Latent Tokenization This paper develops a self-supervised representation learning approach based on pointwise mutual information factorisation for scalable generative latent tokenization. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on representation learning efficiency, not deployment safety or guardrails.
Generative Representation Learning for Scalable Latent Tokenization This paper develops a self-supervised representation learning approach based on pointwise mutual information factorisation for scalable generative latent tokenization. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Evaluates image tokenizers, not LLM benchmarks or evaluation methods.
Reliability-Aware Multimodal Sentiment Prediction Under Local Modality Missingness This paper introduces RM-Net, a reliability-aware network designed to maintain multimodal sentiment prediction accuracy when spans of modalities are missing. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Sentiment prediction from speech/video, not industrial manufacturing vision.
Speculative Sampling in Interactive Video Generation This paper proposes Speculative Sampling to combine large bidirectional sampling windows with low-latency interaction in interactive video generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Interactive video generation sampling, not industrial quality control.

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