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
Building age estimation based on widely available multi-source1 geospatial data The paper introduces a deep learning framework to estimate building ages from publicly accessible satellite imagery and digital surface models. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with remote sensing and geospatial data fusion rather than vision-language multimodal models.
Building age estimation based on widely available multi-source1 geospatial data The paper introduces a deep learning framework to estimate building ages from publicly accessible satellite imagery and digital surface models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on satellite and geospatial imagery, which is excluded from industrial vision.
Anomaly-Guided Observation and Two-Level Semantic Feedback for Training-Free Video Anomaly Analysis The paper presents a training-free semantic feedback framework using vision-language models to iteratively detect and explain video anomalies. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on generic video anomaly understanding, not industrial manufacturing inspection.
SyncReward: Human-Aligned Synchronization Reward for Audio-Visual Generation The paper introduces a human-annotated dataset, benchmark, and reward model to improve temporal synchronization in audio-visual generation systems. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on audio-visual generation synchronization, not industrial inspection or defect detection.
VideoSlate: Stateful Commit Control for Temporally Grounded Agentic Video Reasoning The paper introduces a stateful commit-control framework with an evidence blackboard to manage revisions during agentic video reasoning. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on video question answering, not industrial defect inspection.
From Sound to Sense: An Anatomy of Semantic Supervision for Speech-Driven Visual Grounding in Remote Sensing Imagery The paper analyzes semantic supervision mechanisms in direct speech-to-box grounding models for remote sensing imagery. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on remote sensing target localization, not industrial defect detection.
Throwing4: Phase-Aware Pose Modeling for Throw-Distance Prediction in Elite Athletics The paper presents a phase-aware pose modeling framework and dataset to predict throw distances in elite athletic competitions from broadcast video. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on pose regression for athletics without multimodal vision-language interaction.
Throwing4: Phase-Aware Pose Modeling for Throw-Distance Prediction in Elite Athletics The paper presents a phase-aware pose modeling framework and dataset to predict throw distances in elite athletic competitions from broadcast video. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on sports biomechanics, not industrial manufacturing defect detection.
Recovering from Pose-Selection Failures in Repeated Visual Localization The paper proposes a history-guided pose reselection technique to correct visual localization errors caused by repetitive environmental structures. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on visual odometry and localization without multimodal language integration.
Recovering from Pose-Selection Failures in Repeated Visual Localization The paper proposes a history-guided pose reselection technique to correct visual localization errors caused by repetitive environmental structures. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on robotics visual localization, not industrial quality inspection.
Learning $ω$-Powered Conditional Distributions with Importance-Weighted Flow Matching The paper introduces an importance-weighted flow matching approach to explicitly learn powered conditional distributions without standard classifier-free guidance. Peer-reviewed	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Not about AI safety, hallucination, or deployment guardrails.
Learning $ω$-Powered Conditional Distributions with Importance-Weighted Flow Matching The paper introduces an importance-weighted flow matching approach to explicitly learn powered conditional distributions without standard classifier-free guidance. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on generative flow matching theory, not industrial inspection.
Learning $ω$-Powered Conditional Distributions with Importance-Weighted Flow Matching The paper introduces an importance-weighted flow matching approach to explicitly learn powered conditional distributions without standard classifier-free guidance. Peer-reviewed	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Focuses on generative flow algorithms rather than LLM benchmarking.
Learning $ω$-Powered Conditional Distributions with Importance-Weighted Flow Matching The paper introduces an importance-weighted flow matching approach to explicitly learn powered conditional distributions without standard classifier-free guidance. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on flow matching sampling mathematics, not multimodal architectures.
Learning $ω$-Powered Conditional Distributions with Importance-Weighted Flow Matching The paper introduces an importance-weighted flow matching approach to explicitly learn powered conditional distributions without standard classifier-free guidance. Peer-reviewed	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Not focused on small models, distillation, or efficient inference.
Federated Coreset Subsampling for Distributed Memory Banks The paper proposes federated coreset subsampling strategies to enable distributed, privacy-preserving visual anomaly detection across multiple factory sites. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on federated visual anomaly detection without multimodal language integration.
Pixels or Code? Benchmarking Instruction-Guided Visual Artifact Operation The paper introduces a benchmark to evaluate direct edits, dependency updates, and visual preservation on technical diagrams, charts, and documents. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on visual artifact operation, not industrial defect inspection.
Tikhonov-Stabilized Bezier Representation Forecasting for Training-free Diffusion Acceleration The paper proposes a training-free framework that accelerates diffusion inference by forecasting intermediate representations using low-order Bezier trajectories. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on accelerating diffusion models, not industrial defect detection.
Tikhonov-Stabilized Bezier Representation Forecasting for Training-free Diffusion Acceleration The paper proposes a training-free framework that accelerates diffusion inference by forecasting intermediate representations using low-order Bezier trajectories. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on cache forecasting for diffusion acceleration without multimodal models.
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	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on distillation for face forgery detection rather than multimodal reasoning.
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	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on surveillance crime video anomaly detection, not manufacturing quality control.
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.
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	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses strictly on 3D CT medical image segmentation without multimodal models.
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.
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	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	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	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	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	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	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.
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.
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.

9,901–9,960 of 17,313← Previous Next →