Every paper checked — nothing hidden

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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
VisibilitySplat: Ray-Traced Occlusion for Relighting with 3D Gaussian Splatting Combines 3D Gaussian Splatting with ray-traced occlusion estimation to enable relighting and material decomposition. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Computer graphics inverse rendering, not multimodal text-image intelligence.
OmniPoser: Flexible Human Motion Recovery in the Wild with Masked Flow Matching Recovers full-body human motion from flexible sensor subsets using a cross-modal masking mechanism and single-step flow matching. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on wearable sensor fusion and 3D motion, not multimodal models.
OmniPoser: Flexible Human Motion Recovery in the Wild with Masked Flow Matching Recovers full-body human motion from flexible sensor subsets using a cross-modal masking mechanism and single-step flow matching. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Human pose recovery from wearables, not industrial visual quality control.
CoDy: Codec Dynamics as Complementary Priors for Unsupervised Temporal Action Localization Integrates video codec dynamics with visual features to improve unsupervised temporal action localization without manual annotations. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Video temporal action localization, not manufacturing or defect inspection.
CoDy: Codec Dynamics as Complementary Priors for Unsupervised Temporal Action Localization Integrates video codec dynamics with visual features to improve unsupervised temporal action localization without manual annotations. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Processes video codecs and RGB, not text-vision multimodal LLMs.
BluePixel: Toward Native 4K Agentic Image Editing Combines an adapted editing model with an agent harness to perform instruction-driven four-kilopixel image editing. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on 4K photo editing, not industrial manufacturing inspection.
On the Limits of Representation-Based Test-Time Adaptation for Multimodal LLMs Analyzes why feature-based test-time adaptation fails to recover accuracy on corrupted inputs in generative multimodal language models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Studies multimodal LLM adaptation, not industrial defect detection.
On the Limits of Representation-Based Test-Time Adaptation for Multimodal LLMs Analyzes why feature-based test-time adaptation fails to recover accuracy on corrupted inputs in generative multimodal language models. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Investigates representation adaptation failure, not compression or efficient inference.
CARD: Closing the Teacher-Student Loop for Adversarial Robustness Distillation Develops a closed-loop distillation pipeline where student feedback refines teacher models to improve adversarial robustness. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Theoretical adversarial distillation method, not industrial computer vision.
CARD: Closing the Teacher-Student Loop for Adversarial Robustness Distillation Develops a closed-loop distillation pipeline where student feedback refines teacher models to improve adversarial robustness. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant General vision distillation, not cross-modal multimodal models.
CARD: Closing the Teacher-Student Loop for Adversarial Robustness Distillation Develops a closed-loop distillation pipeline where student feedback refines teacher models to improve adversarial robustness. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Focuses on training distillation, not LLM benchmark evaluation.
Quantifying Annotation Agreement in Object Detection with Optimal Transport Applies optimal transport metrics to quantify graded annotation agreement and label discrepancies in object detection datasets. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on 2D bounding box evaluation, not multimodal models.
Quantifying Annotation Agreement in Object Detection with Optimal Transport Applies optimal transport metrics to quantify graded annotation agreement and label discrepancies in object detection datasets. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant General object detection metric, not specific to industrial inspection.
SAM3RL: Memory Control via Reinforcement Learning for Visual Object Tracking Trains a reinforcement learning controller to manage frame memory dynamically for visual object tracking in foundation models. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Focuses on memory management for tracking models, not LLM evaluation or benchmarks.
SAM3RL: Memory Control via Reinforcement Learning for Visual Object Tracking Trains a reinforcement learning controller to manage frame memory dynamically for visual object tracking in foundation models. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Studies visual memory controllers in tracking models, not language model compression or inference efficiency.
SAM3RL: Memory Control via Reinforcement Learning for Visual Object Tracking Trains a reinforcement learning controller to manage frame memory dynamically for visual object tracking in foundation models. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Addresses visual object tracking and video segmentation, not multimodal language-vision reasoning.
SAM3RL: Memory Control via Reinforcement Learning for Visual Object Tracking Trains a reinforcement learning controller to manage frame memory dynamically for visual object tracking in foundation models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Addresses visual object tracking in generic videos, not industrial inspection or defect detection.
SAM3RL: Memory Control via Reinforcement Learning for Visual Object Tracking Trains a reinforcement learning controller to manage frame memory dynamically for visual object tracking in foundation models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Deals with reinforcement learning for video tracking memory, not deployment safety or guardrails.
Instruction Mining From Images: Constructing a Synthetic Dataset for Multimodal Learning ILSP DCVLR Competition Submission Generates a filtered synthetic dataset of image-based instruction-response pairs for training multimodal reasoning models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Develops synthetic instruction datasets for multimodal models, not industrial visual inspection.
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.
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.
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	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Addresses surgical planning digital twins for ventricular shunts, not industrial inspection.
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.
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	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on reinforcement learning preference aggregation for video generation, not multimodal models.
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.
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	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	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	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	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	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	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on generative video diffusion distillation rather than multimodal language-vision models.
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.
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	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	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	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	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	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	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Analyzes image classification filters rather than model compression, quantization, or efficient serving.
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.
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.

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