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
Not Every Cue Is Evidence: Cue Supportability for Forensic Distillation in Face Forgery Detection The paper presents a dual supportability audit to filter ungrounded cues during forensic distillation for face forgery detection. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on face forgery detection, not industrial manufacturing inspection.
GHOST: Geometry-Constrained Hybrid Diffusion for Open-Vocabulary 3D Scene Graph Generation The paper proposes a hybrid diffusion method that enforces geometric constraints to generate open-vocabulary 3D scene graphs from point clouds. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D scene graphs, not industrial visual inspection.
Teaching Vision-Language Models to Decline: Support Completion Against Mirage The paper proposes a training method that teaches vision-language models to decline to answer when relevant visual evidence is missing. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on general vision-language question answering, not industrial vision.
Auditing Observation-Quality Shortcuts in the Evaluation of Person-Centered Motion for Video Anomaly Detection The paper presents an evaluation framework showing that observation-quality shortcuts can bias motion-based video anomaly detection benchmarks. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on pose-based video anomaly evaluation without multimodal language integration.
Auditing Observation-Quality Shortcuts in the Evaluation of Person-Centered Motion for Video Anomaly Detection The paper presents an evaluation framework showing that observation-quality shortcuts can bias motion-based video anomaly detection benchmarks. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on surveillance crime video anomaly detection, not manufacturing quality control.
MiMaAlign: Hierarchical Micro-Macro Alignment for Physically Plausible Video Generation The paper proposes a hierarchical alignment method that transfers continuous dynamics and high-level event knowledge into video diffusion models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on text-to-video diffusion, not industrial visual inspection.
Self-Verifier Capture in Unified Visual Generators: Diagnosing and Repairing Closed-Loop Self-Reward The paper analyzes failure modes in unified visual generators using self-reward loops and proposes stabilization methods to prevent quality degradation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on visual generative models, not industrial inspection.
KARAMEL: Knowledge-Aware Ranking for Multimodal Entity Linking in the Arts via Heterogeneous Graphs The paper introduces a multimodal entity linking method that combines vision-language models with heterogeneous graph networks for cultural heritage data. Peer-reviewed	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Not focused on deployment safety, jailbreaks, or guardrails.
KARAMEL: Knowledge-Aware Ranking for Multimodal Entity Linking in the Arts via Heterogeneous Graphs The paper introduces a multimodal entity linking method that combines vision-language models with heterogeneous graph networks for cultural heritage data. Peer-reviewed	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Not about language model benchmark methodologies or LLM evaluation.
KARAMEL: Knowledge-Aware Ranking for Multimodal Entity Linking in the Arts via Heterogeneous Graphs The paper introduces a multimodal entity linking method that combines vision-language models with heterogeneous graph networks for cultural heritage data. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on art history entity linking, not industrial inspection.
KARAMEL: Knowledge-Aware Ranking for Multimodal Entity Linking in the Arts via Heterogeneous Graphs The paper introduces a multimodal entity linking method that combines vision-language models with heterogeneous graph networks for cultural heritage data. Peer-reviewed	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Not about small language models or efficient inference techniques.
Deep Learning-based Mechanical Characterization of Synthetically Generated Plant Fibers under Transverse Compression The paper introduces a deep learning framework to rapidly simulate stress fields and mechanical properties of compressed plant fibers. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on surrogate neural networks for mechanical compression, not multimodal models.
Deep Learning-based Mechanical Characterization of Synthetically Generated Plant Fibers under Transverse Compression The paper introduces a deep learning framework to rapidly simulate stress fields and mechanical properties of compressed plant fibers. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on materials science finite element surrogate modeling, not visual inspection.
NoduleFlow: Automatic 3D Lung Nodule Detection and Segmentation The paper presents a unified deep learning framework for the automatic detection, classification, and segmentation of lung nodules directly from CT scans. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical CT lung nodule detection, not industrial vision.
NoduleFlow: Automatic 3D Lung Nodule Detection and Segmentation The paper presents a unified deep learning framework for the automatic detection, classification, and segmentation of lung nodules directly from CT scans. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses strictly on 3D CT medical image segmentation without multimodal models.
Dense Endoluminal Mapping and Localisation from Monocular Bronchoscopy The paper introduces a monocular vision system to track bronchoscope tip location and map airway surfaces using standard RGB video alone. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical endoscopy SLAM, not industrial inspection.
Dense Endoluminal Mapping and Localisation from Monocular Bronchoscopy The paper introduces a monocular vision system to track bronchoscope tip location and map airway surfaces using standard RGB video alone. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on monocular SLAM without vision-language or multimodal integration.
CineRecon: Benchmarking Frontier Models for Agentic Cinematic Reconstruction The paper presents a benchmark to test how well AI agents can reconstruct dynamic, editable 3D scenes from dynamic reference videos. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on cinematic 3D reconstruction, not industrial inspection.
Variational Filtering for Bayesian Last Layers with an Independent Binary Probit Surrogate The paper proposes a closed-form variational filtering algorithm for the last layer of deep classifiers to improve uncertainty calibration. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Not about industrial inspection or manufacturing defect detection.
Variational Filtering for Bayesian Last Layers with an Independent Binary Probit Surrogate The paper proposes a closed-form variational filtering algorithm for the last layer of deep classifiers to improve uncertainty calibration. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Not about deployment safety, guardrails, or hallucination mitigation.
Variational Filtering for Bayesian Last Layers with an Independent Binary Probit Surrogate The paper proposes a closed-form variational filtering algorithm for the last layer of deep classifiers to improve uncertainty calibration. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on deep classifier Bayesian layers, not multimodal models.
Variational Filtering for Bayesian Last Layers with an Independent Binary Probit Surrogate The paper proposes a closed-form variational filtering algorithm for the last layer of deep classifiers to improve uncertainty calibration. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Not about LLM evaluation or benchmark methodology.
Variational Filtering for Bayesian Last Layers with an Independent Binary Probit Surrogate The paper proposes a closed-form variational filtering algorithm for the last layer of deep classifiers to improve uncertainty calibration. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Not focused on model compression, quantization, or efficient serving.
Code-Interactive Visual Reasoning for Financial Candlestick Understanding The paper introduces a model and dataset for financial candlestick reasoning by generating and executing code to gather visual evidence. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Does not study model compression, distillation, or efficient inference serving.
Code-Interactive Visual Reasoning for Financial Candlestick Understanding The paper introduces a model and dataset for financial candlestick reasoning by generating and executing code to gather visual evidence. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on financial chart reasoning, not industrial manufacturing vision.
Code-Interactive Visual Reasoning for Financial Candlestick Understanding The paper introduces a model and dataset for financial candlestick reasoning by generating and executing code to gather visual evidence. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Examines visual financial reasoning, not deployment safety or jailbreak guardrails.
Code-Interactive Visual Reasoning for Financial Candlestick Understanding The paper introduces a model and dataset for financial candlestick reasoning by generating and executing code to gather visual evidence. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Introduces a financial reasoning benchmark, but primary focus is multimodal code-interactive chart reasoning.
JtT: Rethinking Point Trajectory Diffusion for Diverse and Rigid Motion from an Image The paper presents a diffusion transformer operating on per-frame velocities to generate rigid point trajectories from a single image. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Focuses on point trajectory diffusion generation, not LLM benchmark evaluation.
JtT: Rethinking Point Trajectory Diffusion for Diverse and Rigid Motion from an Image The paper presents a diffusion transformer operating on per-frame velocities to generate rigid point trajectories from a single image. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Not related to AI safety, hallucinations, jailbreaks, or guardrails.
JtT: Rethinking Point Trajectory Diffusion for Diverse and Rigid Motion from an Image The paper presents a diffusion transformer operating on per-frame velocities to generate rigid point trajectories from a single image. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Investigates diffusion model parameterization, not model quantization or pruning.
JtT: Rethinking Point Trajectory Diffusion for Diverse and Rigid Motion from an Image The paper presents a diffusion transformer operating on per-frame velocities to generate rigid point trajectories from a single image. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies general motion trajectory diffusion, not industrial defect inspection.
JtT: Rethinking Point Trajectory Diffusion for Diverse and Rigid Motion from an Image The paper presents a diffusion transformer operating on per-frame velocities to generate rigid point trajectories from a single image. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Purely visual point trajectory forecasting without multimodal text or language integration.
Uncertainty-Aware Cortical Surface Reconstruction and Spherical Registration for Heterogeneous Brain MRI The paper proposes a neural network trained on synthetic MRI scans to perform cortical surface reconstruction and uncertainty estimation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on clinical brain MRI reconstruction, not manufacturing quality control.
Uncertainty-Aware Cortical Surface Reconstruction and Spherical Registration for Heterogeneous Brain MRI The paper proposes a neural network trained on synthetic MRI scans to perform cortical surface reconstruction and uncertainty estimation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Concerns specialized biomedical image reconstruction, not multimodal vision-language models.
Detecting Chain-of-Thought Hijacking in Backdoored Multimodal Large Reasoning Models The paper introduces a method to detect adversarial chain-of-thought hijacking in backdoored multimodal reasoning models by monitoring reasoning dynamics. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies backdoor attacks in reasoning models, not industrial defect detection.
Adaptive Interaction Network for Human Motion Prediction During Human-Robot Collaboration The paper proposes a dual-branch interaction network to model human-robot spatial interactions for predicting human motion during collaboration. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies human-robot collaborative motion prediction, not industrial visual inspection.
Adaptive Interaction Network for Human Motion Prediction During Human-Robot Collaboration The paper proposes a dual-branch interaction network to model human-robot spatial interactions for predicting human motion during collaboration. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Covers trajectory forecasting in robotics, not multimodal vision-language models.
Language2Drive: Do Vision-Language-Action Models Really Follow the Instructions in Autonomous Driving? The paper introduces a counterfactual benchmark to evaluate whether vision-language-action driving models truly follow natural language instructions. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Explicitly concerns autonomous driving, which is excluded from industrial vision.
Revisiting Natural Language Prompts from Large Language Models for Open-Vocabulary Video Recognition The paper presents a framework exploring category, video, and frame prompts to enhance vision-language models for open-vocabulary video recognition. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Targets open-vocabulary video classification, not manufacturing defect detection.
EvoSpatial: Experience-Driven Skill and Tool Evolution for Spatial Reasoning Agents The paper proposes a framework that evolves a reusable library of skills and tools based on experience for spatial reasoning agents. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses spatial reasoning benchmarks, not industrial visual inspection.
3D-VITAL: Visibility-aware Identity Training from Artificial Liftings of 3D Reconstruction model for Cross-View Object Re-Identification The paper presents a method using 3D mesh reconstruction and visibility-aware training to improve cross-view object re-identification. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Concerns object re-identification across viewpoints, not manufacturing quality control.
3D-VITAL: Visibility-aware Identity Training from Artificial Liftings of 3D Reconstruction model for Cross-View Object Re-Identification The paper presents a method using 3D mesh reconstruction and visibility-aware training to improve cross-view object re-identification. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on single-modality 3D reconstruction and ReID, not multimodal models.
PathPilot: An Adaptive Question-Conditioned Multi-Magnification Navigation Agent for Whole-Slide Image Analysis The paper proposes an adaptive whole-slide image navigation agent that models cross-magnification localization for pathology diagnosis. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical histopathology slide examination, not industrial manufacturing.
FoveaTree: Information-Density Trees for Query-Guided Visual Token Pruning in Video Large Language Models The paper introduces a training-free visual token pruning framework using information-density trees to speed up video large language model inference. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses video large language model token pruning, not industrial inspection.
The Midas Touch for Metric Depth: Interpretable Metricization for Generalizable Depth Perception The paper introduces a hybrid framework combining explicit depth metricization with data-driven refinement to recover metric depth from relative estimates. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Covers monocular metric depth perception, not industrial defect detection.
The Midas Touch for Metric Depth: Interpretable Metricization for Generalizable Depth Perception The paper introduces a hybrid framework combining explicit depth metricization with data-driven refinement to recover metric depth from relative estimates. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Standard single-modality 3D vision estimation, not multimodal reasoning.
Image Tokenizers Should Be Trained Between Images The paper presents a method that fine-tunes image tokenizers on interpolated latent codes to reduce decoding artifacts in diffusion generation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on vision tokenizers for image generation rather than multimodal reasoning.
Image Tokenizers Should Be Trained Between Images The paper presents a method that fine-tunes image tokenizers on interpolated latent codes to reduce decoding artifacts in diffusion generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Concerns latent diffusion image generation, not industrial visual inspection.
Towards Complementary Keypoint Detection via Mixture of Detectors The paper presents a framework that distills multiple keypoint detectors and dynamically routes them per patch for dense image matching. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with general geometric keypoint matching, not industrial quality inspection.
Towards Complementary Keypoint Detection via Mixture of Detectors The paper presents a framework that distills multiple keypoint detectors and dynamically routes them per patch for dense image matching. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses purely on geometric vision detectors, not multimodal models.
ViewStruct: View-Grounded Articulation and Connectivity Inference The paper proposes a vision-language framework to predict rigid-body connectivity and articulation parameters of objects from single views. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses 3D object articulation for robotics, not manufacturing defect detection.
X-Ragent: Tool-Augmented Reinforcement Learning for Evidence-Grounded Chest X-Ray Reasoning The paper introduces a tool-augmented reinforcement learning framework for evidence-grounded chest X-ray diagnostic reasoning. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Applies to medical chest X-ray interpretation, not industrial manufacturing inspection.
Carve VFM: Carving Specialists out of Generalists, Automatic Task-Specific Compression of Vision Foundation Models The paper proposes a structured pruning method to compress vision foundation models into compact task-specific models under parameter budgets. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on vision foundation model compression, not industrial quality control.
Carve VFM: Carving Specialists out of Generalists, Automatic Task-Specific Compression of Vision Foundation Models The paper proposes a structured pruning method to compress vision foundation models into compact task-specific models under parameter budgets. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses broadly on vision model pruning rather than multimodal text-image interactions.
Carve VFM: Carving Specialists out of Generalists, Automatic Task-Specific Compression of Vision Foundation Models The paper proposes a structured pruning method to compress vision foundation models into compact task-specific models under parameter budgets. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Introduces a pruning technique, not LLM benchmarks or evaluation methods.
Carve VFM: Carving Specialists out of Generalists, Automatic Task-Specific Compression of Vision Foundation Models The paper proposes a structured pruning method to compress vision foundation models into compact task-specific models under parameter budgets. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant About model compression efficiency, not AI safety, hallucination, or alignment.
A Multi-Task Deep Learning Framework for Pose-Invariant Face Recognition and Facial Landmark Localization The paper presents a dual-branch neural network designed to simultaneously perform pose-invariant face recognition and facial landmark localization. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Standard computer vision task on facial images, not multimodal models.
A Multi-Task Deep Learning Framework for Pose-Invariant Face Recognition and Facial Landmark Localization The paper presents a dual-branch neural network designed to simultaneously perform pose-invariant face recognition and facial landmark localization. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses face recognition and landmark localization, not industrial defect detection.
Vision Models Capture Complementary Representations in Children That Converge in Adults The paper uses EEG data to compare how image-text aligned and vision-only models align with developing human visual representations. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Examines human developmental neuroscience representations, not industrial computer vision.
From Volpiano to Pixels: 30,000 Lines of OMR Ground Truth for Medieval Chant The paper introduces an optical music recognition dataset and pipeline linking medieval chant manuscript images to musical target tokens. Preprint	Retrieval-augmented generation (RAG) via arxiv · 15 Oct, 06:18	Not relevant About optical music recognition, not retrieval-augmented generation systems.

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