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
MORE: Learning Motion-Oriented Registers for Driving World Models and Planning The paper proposes learning motion-oriented register tokens during video pretraining to provide compact state representations for driving world models. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Autonomous driving representation learning, not general multimodal models across modalities.
MORE: Learning Motion-Oriented Registers for Driving World Models and Planning The paper proposes learning motion-oriented register tokens during video pretraining to provide compact state representations for driving world models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Autonomous driving world models, not industrial inspection or defect detection.
Scalable Multi-Human Cooperative Manipulation via Commander-Executor Coordination The paper introduces a hierarchical commander-executor framework to coordinate multi-agent cooperative object manipulation tasks in physics simulations. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant General robotics manipulation, not manufacturing visual inspection.
Scalable Multi-Human Cooperative Manipulation via Commander-Executor Coordination The paper introduces a hierarchical commander-executor framework to coordinate multi-agent cooperative object manipulation tasks in physics simulations. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Humanoid robotics control and planning, not multimodal foundation models.
Engram Neuron Inspired Adaptive Memorization for Lifelong Learning The paper proposes an engram-neuron-inspired memory framework using gradient representations to regulate updates in lifelong learning. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on general lifelong learning algorithms, not multimodal modeling.
Engram Neuron Inspired Adaptive Memorization for Lifelong Learning The paper proposes an engram-neuron-inspired memory framework using gradient representations to regulate updates in lifelong learning. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant General lifelong learning algorithm, not industrial visual defect detection.
Text-Guided Medical Image Segmentation via Residual Aggregation and Dense Alignment Representations The paper presents a parameter-efficient architecture connecting text embeddings with mask decoding for language-guided medical image segmentation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Medical image segmentation, not industrial defect or manufacturing inspection.
DSM-Free UAV Visual Localization via Latent-Depth Variable Projection and Structure-Adaptive Coupling The paper proposes an analytical projection method for drone visual localization over 2D maps without digital surface models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on UAV visual localization, not industrial defect detection.
DSM-Free UAV Visual Localization via Latent-Depth Variable Projection and Structure-Adaptive Coupling The paper proposes an analytical projection method for drone visual localization over 2D maps without digital surface models. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Presents geometric localization for UAVs, not multimodal models.
CatPortrait: Taming Video Generative Models for Portrait Animation via In-context Conditioning The paper presents a framework that uses structured 3D facial guidance as in-context input conditioning for controllable portrait video animation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Portrait animation generation, not industrial visual quality control.
AD-GS: Anatomical Density-guided 3D Gaussian Splatting for Sparse-View Dental CBCT Reconstruction The paper proposes an anatomical density-guided 3D Gaussian splatting method for sparse-view dental computed tomography reconstruction. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Medical 3D reconstruction method, not a multimodal reasoning model.
AD-GS: Anatomical Density-guided 3D Gaussian Splatting for Sparse-View Dental CBCT Reconstruction The paper proposes an anatomical density-guided 3D Gaussian splatting method for sparse-view dental computed tomography reconstruction. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on dental CBCT medical imaging, not industrial quality inspection.
Metric-Driven Reinforcement Learning for Object Hallucination Reduction in LVLM-Based Image Captioning The paper proposes a reinforcement learning framework using natural language metrics to reduce object hallucination in vision-language image captioning. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on image captioning hallucination, not industrial defect detection.
Metric-Driven Reinforcement Learning for Object Hallucination Reduction in LVLM-Based Image Captioning The paper proposes a reinforcement learning framework using natural language metrics to reduce object hallucination in vision-language image captioning. Peer-reviewed	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Focuses on hallucination mitigation rather than small or efficient architectures.
Metric-Driven Reinforcement Learning for Object Hallucination Reduction in LVLM-Based Image Captioning The paper proposes a reinforcement learning framework using natural language metrics to reduce object hallucination in vision-language image captioning. Peer-reviewed	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Focuses on RL training to reduce hallucination, not benchmark evaluation.
Retraining-Free Depth Pruning of Vision Transformers: A Cross Domain Study of Layer Redundancy The paper evaluates layer input-output cosine similarity to prune redundant layers in vision transformers without retraining. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on pruning unimodal vision transformers, not multimodal models.
Retraining-Free Depth Pruning of Vision Transformers: A Cross Domain Study of Layer Redundancy The paper evaluates layer input-output cosine similarity to prune redundant layers in vision transformers without retraining. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant General vision transformer pruning, not specific to industrial manufacturing inspection.
CowCare: A Unified Visual Framework for Viewpoint-Robust Cattle Tracking and Spatiotemporal Heat-Stress Analysis The paper presents a visual tracking and analysis framework for multi-camera cattle monitoring and heat-stress detection. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with video-based tracking, not multimodal language-vision models.
CowCare: A Unified Visual Framework for Viewpoint-Robust Cattle Tracking and Spatiotemporal Heat-Stress Analysis The paper presents a visual tracking and analysis framework for multi-camera cattle monitoring and heat-stress detection. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on livestock tracking in agriculture, not industrial manufacturing.
Appearance Compensation in Volume Rendering The paper theoretically analyzes whether volume rendering with independent sources can reproduce external views while maintaining incorrect internal density. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Theoretical physics of volume rendering, not multimodal AI.
Appearance Compensation in Volume Rendering The paper theoretically analyzes whether volume rendering with independent sources can reproduce external views while maintaining incorrect internal density. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Theoretical volume rendering physics, not industrial visual quality control.
What Really Works for Universal Multimodal Embeddings? A Controlled Study of Contrastive Training Strategies The paper conducts a controlled benchmark study evaluating common contrastive training strategies for universal multimodal embedding learning. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates multimodal representation learning, not industrial inspection.
Use Of Convolutional Neural Networks In Detection Of Branch Dieback Disease In Pequi Trees The paper compares five convolutional neural network architectures for detecting branch dieback disease in pequi tree images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on unimodal computer vision for plant disease diagnosis.
Use Of Convolutional Neural Networks In Detection Of Branch Dieback Disease In Pequi Trees The paper compares five convolutional neural network architectures for detecting branch dieback disease in pequi tree images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on agricultural tree disease detection, not industrial manufacturing.
Global Disaster Risk Assessment Using World Risk Index Data: A Geospatial and Visual Analytics Approach The paper analyzes historical World Risk Index data using Python visual analytics libraries to assess global natural disaster vulnerabilities. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on global disaster risk analytics, not industrial inspection.
Global Disaster Risk Assessment Using World Risk Index Data: A Geospatial and Visual Analytics Approach The paper analyzes historical World Risk Index data using Python visual analytics libraries to assess global natural disaster vulnerabilities. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Geospatial data visualization, not multimodal vision-language models.
BrainAid: Efficient Brain Tumor Detection Using Lightweight CNNs and Explainable AI for Resource-Constrained Environments The paper evaluates lightweight convolutional networks and vision transformers for multi-class brain tumor classification from MRI scans. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on unimodal vision classification for medical imaging.
BrainAid: Efficient Brain Tumor Detection Using Lightweight CNNs and Explainable AI for Resource-Constrained Environments The paper evaluates lightweight convolutional networks and vision transformers for multi-class brain tumor classification from MRI scans. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses medical MRI tumor detection, not industrial quality control.
Region Aware Squeeze-and-Excitation Networks for Image Segmentation The paper introduces spatially guided pooling modules to enable region-aware channel recalibration in convolutional networks for image segmentation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses purely on vision segmentation modules, not multimodal data.
Region Aware Squeeze-and-Excitation Networks for Image Segmentation The paper introduces spatially guided pooling modules to enable region-aware channel recalibration in convolutional networks for image segmentation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant General computer vision segmentation architecture, not industrial defect detection.
TIDE: Trajectory-Informed Skill Distillation for Efficient Text-to-Video Prompt Optimization The paper introduces a framework that distills iterative prompt search into rule modules for efficient text-to-video generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with text-to-video generation, not industrial visual inspection.
Generative Quantum Machine Learning Methods for Cancer Detection using Augmented Datasets The paper proposes a generative quantum machine learning method to create synthetic breast ultrasound images for training cancer detection models. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical image classification and quantum ML, not multimodal systems.
Generative Quantum Machine Learning Methods for Cancer Detection using Augmented Datasets The paper proposes a generative quantum machine learning method to create synthetic breast ultrasound images for training cancer detection models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical cancer detection, not industrial manufacturing inspection.
Drive3R: Block-wise Streaming Geometric Foundation Models for Autonomous Driving The paper presents a block-wise streaming geometric foundation model for continuous 3D reconstruction and simulation in autonomous driving. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D geometric reconstruction for driving, not cross-modal models.
Drive3R: Block-wise Streaming Geometric Foundation Models for Autonomous Driving The paper presents a block-wise streaming geometric foundation model for continuous 3D reconstruction and simulation in autonomous driving. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Autonomous driving reconstruction is explicitly excluded from this topic's scope.
RootSLAM: Square Root Bundle Adjustment for Visual-Inertial SLAM The paper introduces a visual-inertial SLAM system that applies square-root bundle adjustment to achieve faster multi-camera tracking on low-power devices. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses geometric visual-inertial SLAM, not multimodal language-vision foundation models.
RootSLAM: Square Root Bundle Adjustment for Visual-Inertial SLAM The paper introduces a visual-inertial SLAM system that applies square-root bundle adjustment to achieve faster multi-camera tracking on low-power devices. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Covers SLAM for robotics, not industrial defect detection or inspection.
TRIG: Toward Measuring Texture Realism in Image Generation The paper proposes an evaluation metric using a texture-trained GAN discriminator backbone to measure texture realism in generated images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates generative image realism, not manufacturing defect detection or inspection.
TRIG: Toward Measuring Texture Realism in Image Generation The paper proposes an evaluation metric using a texture-trained GAN discriminator backbone to measure texture realism in generated images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on computer vision texture metrics, not multimodal integration.
ExeWorldBench: Benchmarking Code-Based Executable 3D World Modeling The paper introduces a benchmark evaluating whether coding agents can construct interactive, code-based 3D simulations that capture underlying physical principles. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on code-based 3D world modeling, not industrial quality control.
Automated carotid artery atherosclerotic inflammation segmentation in PET using MSR-Net The paper presents a two-stage multiscale residual convolutional network to segment and quantify carotid artery atherosclerotic inflammation on PET images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Medical PET/MR imaging, not industrial defect detection.
Automated carotid artery atherosclerotic inflammation segmentation in PET using MSR-Net The paper presents a two-stage multiscale residual convolutional network to segment and quantify carotid artery atherosclerotic inflammation on PET images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Specialized medical image segmentation rather than general multimodal language-vision models.
ASM-6D: Fast Certified Pose-Shape Inference with Complete Correspondence Flow Maps The paper introduces an efficient method that couples generative complete-geometry prediction with active shape models for category-level 6D pose estimation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies robotic grasping and 6D pose estimation, not production line inspection.
ASM-6D: Fast Certified Pose-Shape Inference with Complete Correspondence Flow Maps The paper introduces an efficient method that couples generative complete-geometry prediction with active shape models for category-level 6D pose estimation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant RGB-D 3D pose estimation without multimodal language-vision capabilities.
Channel Match: Calibrating Shape Latents for Few-Step 3D Generation The paper proposes a few-step distillation framework for native 3D generation to mitigate sampling-induced latent drift that damages texture synthesis. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with 3D generative asset modeling, not manufacturing inspection.
Channel Match: Calibrating Shape Latents for Few-Step 3D Generation The paper proposes a few-step distillation framework for native 3D generation to mitigate sampling-induced latent drift that damages texture synthesis. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D latent distillation without multimodal reasoning or language integration.
TempoKV: Predictive KV Cache Quantization for Autoregressive Video Generation The paper presents a predictive KV cache quantization method exploiting temporal predictability to reduce memory overhead in autoregressive video generation models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Video diffusion cache quantization, not industrial anomaly detection.
CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks The paper presents a four-gate verification protocol to evaluate whether audio-conditioned visual prediction models genuinely rely on input audio signals. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Analyzes feature attribution in audio-visual tasks, not LLM safety guardrails.
CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks The paper presents a four-gate verification protocol to evaluate whether audio-conditioned visual prediction models genuinely rely on input audio signals. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates audio-visual prediction checks, not industrial defect detection.
CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks The paper presents a four-gate verification protocol to evaluate whether audio-conditioned visual prediction models genuinely rely on input audio signals. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Addresses audio-visual feature gating, not model compression or efficient serving.
CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks The paper presents a four-gate verification protocol to evaluate whether audio-conditioned visual prediction models genuinely rely on input audio signals. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Tests audio-conditioned vision proxy tasks, not LLM evaluation or benchmarks.
BaT-SAM: Introducing Inductive Bias into SAM via a Mixture of Convolutional Experts for Brain Tumor Segmentation The paper adapts the Segment Anything Model for automated brain tumor segmentation using multi-scale convolutional experts without requiring manual inference prompts. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Medical MRI segmentation, not industrial defect detection.
BaT-SAM: Introducing Inductive Bias into SAM via a Mixture of Convolutional Experts for Brain Tumor Segmentation The paper adapts the Segment Anything Model for automated brain tumor segmentation using multi-scale convolutional experts without requiring manual inference prompts. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Vision-only medical image segmentation without multimodal text-image reasoning.
Video-Based Sexual Harassment Detection Using Fine-Tuned Video Transformers The paper evaluates fine-tuned video transformers on an expanded video dataset to detect instances of sexual harassment for surveillance applications. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Standard video classification without cross-modal interaction or multimodal foundation models.
Video-Based Sexual Harassment Detection Using Fine-Tuned Video Transformers The paper evaluates fine-tuned video transformers on an expanded video dataset to detect instances of sexual harassment for surveillance applications. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on surveillance harassment detection, not industrial defect detection.
UniForge3D: Joint 3D Reconstruction and Generation in a Shared Anchor-Guided Space The paper introduces a method that unifies 3D reconstruction and generation within a shared anchor-guided coordinate space to preserve observed geometry. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D asset generation, not manufacturing defect detection.
UniForge3D: Joint 3D Reconstruction and Generation in a Shared Anchor-Guided Space The paper introduces a method that unifies 3D reconstruction and generation within a shared anchor-guided coordinate space to preserve observed geometry. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Standard 3D computer vision reconstruction without multimodal language integration.
VideoEvoHarness: Self Evolving Agent Harness from Unlabeled Videos for Video Understanding The paper proposes an agent harness that autonomously evolves questioner and solver workflows from unlabeled video data without updating base model parameters. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on video reasoning agents, not industrial production inspection.
OmniRSI: Taming Latent Diffusion for Unified Multimodal Remote Sensing Image Generation The paper proposes a unified latent diffusion architecture with a custom variational autoencoder for multimodal remote sensing image generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Remote sensing imagery, which is explicitly excluded from topic focus.
Harnessing SPAD Noise: Test-Time Gated Attention for Indoor Depth Estimation The paper introduces a lightweight test-time attention framework that leverages single-photon sensor noise as an informative prior for indoor depth estimation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Indoor depth estimation, not industrial inspection or manufacturing lines.

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