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
Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies Examines industrial logical anomaly detection under capture shifts and proposes a reference-free classifier trained on synthetic anomalies. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Main focus is industrial anomaly detection rather than multimodal foundation model architectures.
Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies Examines industrial logical anomaly detection under capture shifts and proposes a reference-free classifier trained on synthetic anomalies. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Evaluates visual anomaly detection methods rather than language model benchmarks or judges.
Omni-RS: Unifying Multi-Task Understanding and Generation in Remote Sensing Presents Omni-RS, a unified framework and dataset supporting multiple remote sensing image understanding and generation tasks. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with remote sensing imagery, not industrial or manufacturing defect detection.
CityCode: Building Agent-Operable 3D Cities from Sparse Aerial Observations Introduces CityCode, an agent-operable representation generating parameterized 3D urban environments from sparse low-altitude aerial images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Covers aerial 3D urban reconstruction, not industrial visual quality control.
CityCode: Building Agent-Operable 3D Cities from Sparse Aerial Observations Introduces CityCode, an agent-operable representation generating parameterized 3D urban environments from sparse low-altitude aerial images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D urban scene reconstruction from imagery without multimodal language interaction.
Visual Sevoing from Lines Presents a visual servoing approach using binormalized Plucker line coordinates to decouple rotation and translation control. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with robot motion control from geometric lines, not multimodal models.
Visual Sevoing from Lines Presents a visual servoing approach using binormalized Plucker line coordinates to decouple rotation and translation control. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on robotic visual servoing control, not industrial defect detection.
Hallucination-aware Faithful Reasoning in Remote Sensing Presents FaithRS, a self-reflection framework with a fine-grained dataset to detect and correct reasoning hallucinations in remote sensing models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on remote sensing reasoning, not industrial defect or quality inspection.
SchemaPose: RGB-Based Category-Level Pose Estimation with Parametric Category Schema Introduces SchemaPose, a schema-guided framework for RGB-based category-level 9D object pose estimation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on general RGB 3D pose estimation, not industrial anomaly detection.
SchemaPose: RGB-Based Category-Level Pose Estimation with Parametric Category Schema Introduces SchemaPose, a schema-guided framework for RGB-based category-level 9D object pose estimation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals purely with single-modality RGB 3D pose estimation without multimodal aspects.
Noise2Match: Self-Supervised Low-Dose CT Denoising via Adaptive Inter-Slice Matching Proposes Noise2Match, a self-supervised low-dose CT denoising method that aligns adjacent slices using adaptive non-rigid matching. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical CT denoising, not industrial inspection or manufacturing.
Noise2Match: Self-Supervised Low-Dose CT Denoising via Adaptive Inter-Slice Matching Proposes Noise2Match, a self-supervised low-dose CT denoising method that aligns adjacent slices using adaptive non-rigid matching. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses medical CT slice denoising without multimodal vision-language integration.
ReDiS: Reasoning-Diagnosis Self-Evolution for Multimodal Reasoning in Remote Sensing Presents ReDiS, a self-evolution framework separating exploration and candidate diagnosis to improve multimodal reasoning in remote sensing. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on remote sensing multimodal reasoning, not manufacturing or industrial vision.
Bifocal: Training-Free Mixed Granularity Visual Token Pruning for Multimodal LLMs Introduces Bifocal, a training-free mixed-granularity visual token pruning method for multimodal models to protect fine-grained task accuracy. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses visual token pruning in MLLMs, not industrial inspection systems.
CoTL: Compact Token Learning for 3D Scene Representation Proposes CoTL, a method to learn compact latent tokens from unposed multi-view images to reconstruct 3D Gaussian scene representations. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D scene representation, not industrial defect detection.
CoTL: Compact Token Learning for 3D Scene Representation Proposes CoTL, a method to learn compact latent tokens from unposed multi-view images to reconstruct 3D Gaussian scene representations. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Covers 3D Gaussian reconstruction without multimodal text, language, or cross-modal components.
EmoGenie: Benchmarking and Evaluating Expressed and Evoked Emotion in T2I Generation with MLLMs Introduces EmoGenie, a benchmark evaluating expressed and evoked emotions in text-to-image generation and multimodal language model understanding. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies emotional evaluation of generated art, not industrial visual inspection.
$\mathrm{S}^3$-PnP: Plug-and-Play Denoising for Scientific Imaging with Self-Supervised Score Priors Proposes a self-supervised plug-and-play restoration framework that learns score priors directly from intermediate states for scientific imaging. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with scientific image denoising rather than multimodal vision-language models.
$\mathrm{S}^3$-PnP: Plug-and-Play Denoising for Scientific Imaging with Self-Supervised Score Priors Proposes a self-supervised plug-and-play restoration framework that learns score priors directly from intermediate states for scientific imaging. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on scientific imaging like MRI, not factory or manufacturing inspection.
MFVSR: A Multi-Style and Fine-Grained Benchmark for Video Subtitle Removal Introduces MFVSR, a multi-style benchmark evaluating localized errors, temporal stability, and reliability in video subtitle removal. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses video subtitle removal, not industrial inspection or defect detection.
MFVSR: A Multi-Style and Fine-Grained Benchmark for Video Subtitle Removal Introduces MFVSR, a multi-style benchmark evaluating localized errors, temporal stability, and reliability in video subtitle removal. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Covers video restoration and inpainting rather than multimodal models or reasoning.
Simplifying and Improving On-Policy Distillation for Few-Step Diffusion Proposes Simplified Matching Distillation, a regression-based on-policy method that enables four-step generation for diffusion models. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Evaluates generative diffusion models, not LLM benchmarks or evaluation methods.
Simplifying and Improving On-Policy Distillation for Few-Step Diffusion Proposes Simplified Matching Distillation, a regression-based on-policy method that enables four-step generation for diffusion models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on generation efficiency, not AI safety, jailbreaks, or deployment guardrails.
Simplifying and Improving On-Policy Distillation for Few-Step Diffusion Proposes Simplified Matching Distillation, a regression-based on-policy method that enables four-step generation for diffusion models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on generative diffusion models, not manufacturing defect detection or inspection.
Physics-Aware Deepfake Detection via Distance-Speech Consistency Detects talking-head deepfakes in dynamic videos by matching speaker distance estimates with distance-dependent acoustic energy variations. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on facial deepfake detection, not industrial manufacturing inspection.
Dual-Domain Sparse-View 4D CBCT Reconstruction with Spatial-Temporal Consistency Learning Presents STCNet, a dual-domain framework using spatial-temporal consistency learning to reconstruct sparse-view 4D CBCT images with fewer projections. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 4D CT reconstruction, not multimodal vision-language models.
Dual-Domain Sparse-View 4D CBCT Reconstruction with Spatial-Temporal Consistency Learning Presents STCNet, a dual-domain framework using spatial-temporal consistency learning to reconstruct sparse-view 4D CBCT images with fewer projections. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical radiotherapy CT reconstruction, not industrial inspection.
Meta-Video: Efficient Standardized Evaluation for Video Understanding Evaluates video benchmarks, showing that unexamined setup choices shift accuracy significantly and proposing a standardized evaluation framework. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates video-language benchmark variance, not industrial inspection.
Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models This paper evaluates whether object pointers from the Segment Anything Model can transfer to downstream clinical tumor prediction tasks. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical image segmentation pointers, not multimodal vision-language models.
Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models This paper evaluates whether object pointers from the Segment Anything Model can transfer to downstream clinical tumor prediction tasks. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Analyzes feature transferability in medical imaging, not LLM evaluation.
Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models This paper evaluates whether object pointers from the Segment Anything Model can transfer to downstream clinical tumor prediction tasks. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on clinical PET/CT tumour prediction, not industrial inspection.
Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models This paper evaluates whether object pointers from the Segment Anything Model can transfer to downstream clinical tumor prediction tasks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Studies medical downstream transfer, not safety guardrails or reliability.
Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models This paper evaluates whether object pointers from the Segment Anything Model can transfer to downstream clinical tumor prediction tasks. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Investigates representation transfer from SAM2, not model efficiency.
Unbalanced W-Flow: Unbalanced Wasserstein Drifting under Finite-Batch Marginal Fluctuations The paper proposes an unbalanced optimal transport method to reduce minibatch fluctuations in teacher-free one-step generative models. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Addresses optimal transport theory, not small model compression.
Unbalanced W-Flow: Unbalanced Wasserstein Drifting under Finite-Batch Marginal Fluctuations The paper proposes an unbalanced optimal transport method to reduce minibatch fluctuations in teacher-free one-step generative models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on theoretical generative modeling, not industrial inspection.
Unbalanced W-Flow: Unbalanced Wasserstein Drifting under Finite-Batch Marginal Fluctuations The paper proposes an unbalanced optimal transport method to reduce minibatch fluctuations in teacher-free one-step generative models. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Discusses mathematical generative dynamics, not multimodal models.
Unbalanced W-Flow: Unbalanced Wasserstein Drifting under Finite-Batch Marginal Fluctuations The paper proposes an unbalanced optimal transport method to reduce minibatch fluctuations in teacher-free one-step generative models. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Covers generative transport theory, not LLM evaluation or benchmarks.
Unbalanced W-Flow: Unbalanced Wasserstein Drifting under Finite-Batch Marginal Fluctuations The paper proposes an unbalanced optimal transport method to reduce minibatch fluctuations in teacher-free one-step generative models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on mathematical divergence optimization, not AI safety guardrails.
Denoise X: Self-Supervised U-Net for Quantum Mottle Suppression in Chest Radiography This paper proposes a lightweight self-supervised neural network trained without clean reference images to reduce noise in chest radiographs. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Investigates medical X-ray restoration, not multimodal language-vision models.
Denoise X: Self-Supervised U-Net for Quantum Mottle Suppression in Chest Radiography This paper proposes a lightweight self-supervised neural network trained without clean reference images to reduce noise in chest radiographs. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical radiography denoising, not industrial inspection.
Observation Quality in DSM-Assisted Aerial Localization: A Benchmark and Base-Anchored Uncertainty Calibration The paper proposes a benchmark and an uncertainty calibration method for aerial map matching in navigation systems. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on aerial drone navigation, not industrial defect detection.
Observation Quality in DSM-Assisted Aerial Localization: A Benchmark and Base-Anchored Uncertainty Calibration The paper proposes a benchmark and an uncertainty calibration method for aerial map matching in navigation systems. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Studies aerial map matching uncertainty calibration, not multimodal models.
Parameter-Efficient Multimodal Brain Tumor Segmentation With Stage-Wise Shared Adapters This paper introduces parameter-efficient shared adapters to combine multiple MRI modalities for brain tumor segmentation with lower complexity. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on multi-sequence MRI image segmentation, not multimodal vision-language models.
Parameter-Efficient Multimodal Brain Tumor Segmentation With Stage-Wise Shared Adapters This paper introduces parameter-efficient shared adapters to combine multiple MRI modalities for brain tumor segmentation with lower complexity. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses clinical brain MRI segmentation, not industrial factory inspection.
Detecting Unreliable Classifications from Quantized Models The paper proposes measuring prediction output agreement between full-precision and quantized models to identify unreliable classifications without ground-truth labels. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on post-training quantization reliability, not multimodal models.
Detecting Unreliable Classifications from Quantized Models The paper proposes measuring prediction output agreement between full-precision and quantized models to identify unreliable classifications without ground-truth labels. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates medical classification models, not industrial quality inspection.
Recasting DiT for Extreme Image Compression with Hierarchical Visual Priors This paper presents a framework adapting diffusion transformers into deterministic, one-step decoders for extreme image compression. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on image compression with diffusion transformers, not multimodal models.
Recasting DiT for Extreme Image Compression with Hierarchical Visual Priors This paper presents a framework adapting diffusion transformers into deterministic, one-step decoders for extreme image compression. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with general image compression, not industrial visual quality control.
VideoJev: System One Model for Video Understanding and Interaction The paper adapts multimodal language models using scoring heads and computation caching for fast video decision-making and interaction. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on video question answering, not industrial defect detection.
MajorTOM:Elliot Pretrain, A Multi-Sensor, Multi-Temporal Pretraining Dataset for Earth Observation This paper introduces a multi-sensor, multi-temporal satellite imagery dataset designed for pretraining Earth observation foundation models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on remote sensing pretraining data, not safety guardrails.
MajorTOM:Elliot Pretrain, A Multi-Sensor, Multi-Temporal Pretraining Dataset for Earth Observation This paper introduces a multi-sensor, multi-temporal satellite imagery dataset designed for pretraining Earth observation foundation models. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Presents an Earth observation dataset, not an LLM benchmark.
MajorTOM:Elliot Pretrain, A Multi-Sensor, Multi-Temporal Pretraining Dataset for Earth Observation This paper introduces a multi-sensor, multi-temporal satellite imagery dataset designed for pretraining Earth observation foundation models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Covers satellite Earth observation datasets, not industrial factory inspection.
MajorTOM:Elliot Pretrain, A Multi-Sensor, Multi-Temporal Pretraining Dataset for Earth Observation This paper introduces a multi-sensor, multi-temporal satellite imagery dataset designed for pretraining Earth observation foundation models. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Focuses on large-scale dataset creation, not model compression.
Grid or Nodes? Probing Object Memory in World Models Under Partial Observability The paper compares spatial feature grids and tracked node coordinates for maintaining object memory under partial robot observability. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Compares spatial memory representations, not small model distillation.
Grid or Nodes? Probing Object Memory in World Models Under Partial Observability The paper compares spatial feature grids and tracked node coordinates for maintaining object memory under partial robot observability. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Studies robot memory representations, not safety guardrails or reliability.
Grid or Nodes? Probing Object Memory in World Models Under Partial Observability The paper compares spatial feature grids and tracked node coordinates for maintaining object memory under partial robot observability. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Examines world model representations in robotics, not multimodal models.
Grid or Nodes? Probing Object Memory in World Models Under Partial Observability The paper compares spatial feature grids and tracked node coordinates for maintaining object memory under partial robot observability. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies robotics world models, not industrial defect inspection.
Grid or Nodes? Probing Object Memory in World Models Under Partial Observability The paper compares spatial feature grids and tracked node coordinates for maintaining object memory under partial robot observability. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Focuses on tracking memory in robotics, not LLM benchmarks.
Texture Interpolation as Texton Matching This paper studies texture interpolation using appearance-aware texton matching instead of standard positional coordinate blending. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Addresses graphic texture interpolation, not safety or deployment reliability.
Texture Interpolation as Texton Matching This paper studies texture interpolation using appearance-aware texton matching instead of standard positional coordinate blending. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses solely on computer graphics texture synthesis, not multimodal models.

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