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
OneSearch-VL: Unified Multimodal Deep Research Agent for Image and Video Introduces a unified multimodal agent using evidence graphs to supervise external retrieval and reasoning across images and videos. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on web-style deep research across images and video, not industrial vision tasks.
Beyond Spatio-Temporal Priors: A Generalizable Approach for Dense Correspondence Matching Presents a dense correspondence framework combining generative and semantic representations to handle non-rigid image editing and generation. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Addresses vision-only dense correspondence matching rather than multimodal cross-modality reasoning.
Beyond Spatio-Temporal Priors: A Generalizable Approach for Dense Correspondence Matching Presents a dense correspondence framework combining generative and semantic representations to handle non-rigid image editing and generation. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:28	Not relevant Focuses on dense correspondence matching techniques rather than general LLM evaluation benchmarks.
Beyond Spatio-Temporal Priors: A Generalizable Approach for Dense Correspondence Matching Presents a dense correspondence framework combining generative and semantic representations to handle non-rigid image editing and generation. Preprint	Small and efficient models via arxiv · 12 Oct, 16:28	Not relevant Does not address model efficiency, distillation, or quantization for small models.
Beyond Spatio-Temporal Priors: A Generalizable Approach for Dense Correspondence Matching Presents a dense correspondence framework combining generative and semantic representations to handle non-rigid image editing and generation. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:28	Not relevant Does not study AI safety, hallucination, guardrails, or deployment reliability risks.
Beyond Spatio-Temporal Priors: A Generalizable Approach for Dense Correspondence Matching Presents a dense correspondence framework combining generative and semantic representations to handle non-rigid image editing and generation. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on dense correspondence matching for image editing and generation, not industrial visual tasks.
Pumpire: Unified Benchmark for Metric Distance Estimation Introduces a benchmark evaluating metric point-to-point distance estimation in 3D foundation models using physical ground-truth measurements. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Evaluates 3D foundation models generally, not focusing on industrial visual inspection or manufacturing.
Pumpire: Unified Benchmark for Metric Distance Estimation Introduces a benchmark evaluating metric point-to-point distance estimation in 3D foundation models using physical ground-truth measurements. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Focuses purely on 3D computer vision metric distance estimation without multimodal integration.
LEGO: A Lifting-Free Approach for Exocentric-to-Egocentric Video Generation Introduces a lifting-free transformer model that directly synthesizes egocentric video from exocentric recordings without explicit 3D reconstruction. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Addresses novel view synthesis for egocentric video rather than industrial computer vision.
One Block, Multiple Depths: Recurrent Vision Transformers with Depth-Programmed Experts Designs a vision transformer using a single recurrent block with depth-programmed experts to reduce stored parameters without accuracy loss. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:28	Not relevant Focuses on architectural parameter efficiency, not AI safety or deployment reliability guardrails.
One Block, Multiple Depths: Recurrent Vision Transformers with Depth-Programmed Experts Designs a vision transformer using a single recurrent block with depth-programmed experts to reduce stored parameters without accuracy loss. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Presents a general computer vision architecture, not an industrial vision application.
One Block, Multiple Depths: Recurrent Vision Transformers with Depth-Programmed Experts Designs a vision transformer using a single recurrent block with depth-programmed experts to reduce stored parameters without accuracy loss. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Focuses on single-modality vision transformer architectures rather than multimodal models.
One Block, Multiple Depths: Recurrent Vision Transformers with Depth-Programmed Experts Designs a vision transformer using a single recurrent block with depth-programmed experts to reduce stored parameters without accuracy loss. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:28	Not relevant Proposes a recurrent architecture rather than an LLM evaluation methodology or benchmark.
Hybrid Cinematography: Previsualizing and Managing Hallucination Risk in Generative Video Reshooting Presents a previsualization workflow combining physical video capture and generative reshooting to evaluate and manage visual hallucination risk. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on film production cinematography workflows rather than industrial computer vision.
OmniCapBench: A Deep-Structured Evaluation Framework for Fine-Grained Audio-Visual Captioning Introduces an audio-visual caption benchmark using atomic evaluation units to evaluate multimodal large language models reliably. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on audio-visual video captioning evaluation, not industrial visual inspection.
WorldGuide: Goal-Directed Video World Model for Procedural Task Execution Presents a closed-loop goal-directed video world model that iteratively plans and realizes atomic steps for procedural tasks. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on generic procedural video generation rather than industrial computer vision tasks.
OuroWorld: Bringing Any 3D World Alive as Diverse, Endlessly Looping 3D Cinemagraphs Generates seamlessly looping 3D cinemagraphs from static 3D Gaussian splats using periodic deformation fields guided by video models. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on 3D cinemagraph generation for computer graphics rather than industrial computer vision.
What 30,000 Hours of Ego-centric Video Does Not Teach Studies how scaling to 30,000 hours of egocentric video affects world model fidelity for agents versus object interactions. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Studies general world model fidelity scaling from ego-centric video, not industrial applications.
Rubric-CEPR: Self-Evolving Image Editing via Reward-Verified Self-Distillation Proposes a self-evolving image editing method using rubric-guided contrastive verification without external reward models or human annotations. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on general instruction-guided image editing rather than industrial inspection or manufacturing.
Dex-One2Many: Learning Dexterous Manipulation from a Single Human Demonstration Learns dexterous manipulation policies from a single human video by abstracting motions into sequential scene graphs for reinforcement learning. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Focuses on reinforcement learning policy acquisition from demonstration rather than multimodal modeling.
Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback Presents an embodied coding agent framework using active physical and visual probing to refine aerial manipulation policies. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Focuses on embodied robotic control programs rather than multimodal foundational model architectures.
Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback Presents an embodied coding agent framework using active physical and visual probing to refine aerial manipulation policies. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:28	Not relevant Does not focus on LLM safety, guardrails, or alignment risks.
Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback Presents an embodied coding agent framework using active physical and visual probing to refine aerial manipulation policies. Preprint	Small and efficient models via arxiv · 12 Oct, 16:28	Not relevant Does not focus on model compression, quantization, or efficient model serving.
Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback Presents an embodied coding agent framework using active physical and visual probing to refine aerial manipulation policies. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:28	Not relevant Proposes an aerial agent framework rather than general LLM evaluation benchmarks.
Scaling Multi-Teacher Distillation for Digital Pathology Introduces an architecture with teacher-specific tokens and mixture-of-experts to scale multi-teacher distillation in digital pathology. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Focuses on unimodal vision encoder distillation for pathology slides rather than multimodal models.
MemReg: Streaming Outdoor LiDAR Point Cloud Registration with Hybrid Memory Buffers Proposes a multi-frame outdoor LiDAR registration network using hybrid feature and pose memory buffers to leverage temporal sequences. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Deals strictly with 3D LiDAR point clouds without cross-modal interaction.
ForcingBooster: Adaptive Patch-wise Denoising for Fast Autoregressive Video Diffusion Introduces an adaptive patch-wise denoising framework that stops easy patches early to speed up autoregressive video diffusion. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on video diffusion generation speedup rather than industrial computer vision tasks.
Feature Competition and Its Representational Origins in Vision Language Models: Evidence from the Stroop Paradigm Benchmarks vision-language models on the Stroop paradigm to evaluate feature competition and text-versus-color bias. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Studies psychological Stroop effect in general VLMs, not industrial computer vision.
WoodBR-Cross: A public wood-image dataset and individual-tree-disjoint benchmark for species identification Presents an image dataset and an individual-tree-disjoint evaluation benchmark for automated wood species identification. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Focuses purely on single-modality wood image classification, not multimodal models.
Bridging Human and Model Attention: Explainability Analysis of CNN, Mamba, and ViT Architectures with Gaze-Based Validation Evaluates explainability methods across CNN, ViT, and Mamba models using eye-tracking gaze data as ground truth. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Analyzes vision architectures on image datasets without multimodal cross-modal modeling.
Bridging Human and Model Attention: Explainability Analysis of CNN, Mamba, and ViT Architectures with Gaze-Based Validation Evaluates explainability methods across CNN, ViT, and Mamba models using eye-tracking gaze data as ground truth. Preprint	Small and efficient models via arxiv · 12 Oct, 16:28	Not relevant Focuses on interpretability and attention maps, not model efficiency or compression.
Bridging Human and Model Attention: Explainability Analysis of CNN, Mamba, and ViT Architectures with Gaze-Based Validation Evaluates explainability methods across CNN, ViT, and Mamba models using eye-tracking gaze data as ground truth. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:28	Not relevant Investigates explainability methods using gaze alignment, not LLM evaluation benchmarks.
Bridging Human and Model Attention: Explainability Analysis of CNN, Mamba, and ViT Architectures with Gaze-Based Validation Evaluates explainability methods across CNN, ViT, and Mamba models using eye-tracking gaze data as ground truth. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Studies attention explainability via eye-tracking, not industrial inspection tasks.
Zebra3D: Efficient Hybrid Foundation Models For Scalable 3D Reconstruction Proposes a hybrid linear and sparse attention framework to accelerate feed-forward 3D foundation models across many views. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Addresses 3D vision reconstruction, not multimodal vision-language reasoning.
Zebra3D: Efficient Hybrid Foundation Models For Scalable 3D Reconstruction Proposes a hybrid linear and sparse attention framework to accelerate feed-forward 3D foundation models across many views. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:28	Not relevant Focuses on computational efficiency and reconstruction accuracy, not safety or guardrails.
Zebra3D: Efficient Hybrid Foundation Models For Scalable 3D Reconstruction Proposes a hybrid linear and sparse attention framework to accelerate feed-forward 3D foundation models across many views. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:28	Not relevant Introduces an efficient model architecture rather than benchmark evaluation frameworks.
Zebra3D: Efficient Hybrid Foundation Models For Scalable 3D Reconstruction Proposes a hybrid linear and sparse attention framework to accelerate feed-forward 3D foundation models across many views. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on general 3D reconstruction foundation models, not industrial inspection.
StereoEngine: Scaling Stereo Bimanual Robot Data without Stereo Cameras Synthesizes stereo manipulation data from monocular robot demonstrations using estimated depth and video diffusion models. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:28	Not relevant Focuses on robotic training data generation, not safety guardrails or reliability monitoring.
StereoEngine: Scaling Stereo Bimanual Robot Data without Stereo Cameras Synthesizes stereo manipulation data from monocular robot demonstrations using estimated depth and video diffusion models. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:28	Not relevant Presents data generation techniques for robotics rather than LLM/AI evaluation benchmarks.
StereoEngine: Scaling Stereo Bimanual Robot Data without Stereo Cameras Synthesizes stereo manipulation data from monocular robot demonstrations using estimated depth and video diffusion models. Preprint	Small and efficient models via arxiv · 12 Oct, 16:28	Not relevant Focuses on synthetic data generation for policy training, not model compression or efficient inference.
Reference-Free Food Volume Estimation from Egocentric Stereo Video Presents an automatic reference-free method to reconstruct and estimate food portion volumes using egocentric stereo video. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Applies to dietary intake monitoring from wearable cameras, not industrial vision.
Reference-Free Food Volume Estimation from Egocentric Stereo Video Presents an automatic reference-free method to reconstruct and estimate food portion volumes using egocentric stereo video. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Uses standard 3D reconstruction and segmentation methods without multimodal cross-modality learning.
Kernelized Parameter Sensitivity Atlases for Amortized Conditional Interpretability Develops a kernelized parameter sensitivity atlas to amortize input-specific gradient attribution across vision, forecasting, and biology models. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Develops general interpretability theory across architectures, not industrial vision systems.
Kernelized Parameter Sensitivity Atlases for Amortized Conditional Interpretability Develops a kernelized parameter sensitivity atlas to amortize input-specific gradient attribution across vision, forecasting, and biology models. Preprint	Small and efficient models via arxiv · 12 Oct, 16:28	Not relevant Focuses on parameter sensitivity attribution, not model compression or efficient serving.
Kernelized Parameter Sensitivity Atlases for Amortized Conditional Interpretability Develops a kernelized parameter sensitivity atlas to amortize input-specific gradient attribution across vision, forecasting, and biology models. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:28	Not relevant Presents an interpretability attribution method rather than a general LLM evaluation benchmark.
Kernelized Parameter Sensitivity Atlases for Amortized Conditional Interpretability Develops a kernelized parameter sensitivity atlas to amortize input-specific gradient attribution across vision, forecasting, and biology models. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Deals with parameter sensitivity atlases, not multimodal fusion or vision-language models.
Shift-Aware Identity-Guided Latent Refinement for Referring Audio--Visual Segmentation Introduces a shift-aware identity-guided latent refinement framework using dual tokens to resolve target drift in referring audio-visual segmentation. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on audio-visual object segmentation, not industrial manufacturing or visual inspection.
Domain Adaptation of SAM 2.1 for Building-Component Segmentation in Image-Based 3D Reconstruction Fine-tunes SAM 2.1 on multi-class building images to improve 2D segmentation for image-based 3D reconstruction. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Applies 2D vision models to 3D radiance fields without multimodal text or audio features.
Spend Where It Matters: Particle Search with MH Refinement for Budget-Constrained Audio-Visual Alignment Presents a training-free framework combining variance-adaptive particle search with Metropolis-Hastings refinement for budget-constrained audio-visual alignment. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Investigates audio-visual generative alignment, not industrial defect detection or robotics perception.
Structure-Aware Matching for Robust UAV Thermal-to-Satellite Geo-Localization Proposes a structure-aware matching framework exploiting directional and low-frequency patterns for UAV thermal-to-satellite geo-localization. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Deals with cross-view thermal-to-optical matching, not multimodal text-image or cross-domain LLMs.
Structure-Aware Matching for Robust UAV Thermal-to-Satellite Geo-Localization Proposes a structure-aware matching framework exploiting directional and low-frequency patterns for UAV thermal-to-satellite geo-localization. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on UAV and satellite geo-localization, not industrial manufacturing or plant inspection.
APEX: Asynchronous Prefix Denoising for Extreme Compression Introduces an asynchronous prefix denoising framework for extreme latent compression in diffusion models. Preprint	LLM evaluation and benchmarks via arxiv · 12 Oct, 16:28	Not relevant Introduces a generative architecture rather than evaluation methodologies or benchmarks.
APEX: Asynchronous Prefix Denoising for Extreme Compression Introduces an asynchronous prefix denoising framework for extreme latent compression in diffusion models. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on general diffusion image generation and latent compression, not industrial vision.
APEX: Asynchronous Prefix Denoising for Extreme Compression Introduces an asynchronous prefix denoising framework for extreme latent compression in diffusion models. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Applies to image autoencoding and generation, not multimodal vision-language models.
APEX: Asynchronous Prefix Denoising for Extreme Compression Introduces an asynchronous prefix denoising framework for extreme latent compression in diffusion models. Preprint	AI safety and reliability in deployment via arxiv · 12 Oct, 16:28	Not relevant Deals with compression efficiency, not AI safety, alignment, or guardrails.
CaptchaAgent: Verifiable Visual Reasoning for CAPTCHA Solving Presents a structured visual reasoning agent that uses intermediate symbolic representations to solve complex visual CAPTCHAs. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Focuses on CAPTCHA solving using web agents, not industrial visual inspection.
Selective Spatio-Temporal Fruit Inspector (S$^2$FI): A Mamba-based Framework for Rotational Fruit Quality Assessment Proposes a lightweight fruit sorting system combining 3D convolutions and Mamba sequence modeling for rotational visual quality inspection. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Focuses purely on video and 3D vision modeling without language or other modal integration.
ROSETTA: Rotation Subspace Estimation for Training-free Transmodal Alignment Presents a training-free calibration layer that aligns mismatched cross-modal embedding spaces via local rotation estimation. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Evaluates autonomous driving sensor alignment, not industrial manufacturing or defect inspection.
ROSETTA: Rotation Subspace Estimation for Training-free Transmodal Alignment Presents a training-free calibration layer that aligns mismatched cross-modal embedding spaces via local rotation estimation. Preprint	Multimodal models via arxiv · 12 Oct, 16:28	Not relevant Addresses sensor coordinate cross-modal alignment without language or multimodal LLM components.
Win-Win Fusion: Multi-Modal Image Fusion with Visual-Semantic Collaboration Develops a multi-modal image fusion framework that combines structural guidance and interactive gated attention to improve perception. Preprint	Computer vision for industrial applications via arxiv · 12 Oct, 16:28	Not relevant Deals with multi-modal image fusion algorithms, not industrial manufacturing or quality control.

15,421–15,480 of 17,313← Previous Next →