Every paper checked — nothing hidden

All papers

Every paper checked in the week of 12–18 Oct 2026 · Multimodal models — nothing is hidden. Brief papers first.

All1,924 In brief3 More (on-topic)553 Not relevant1,333 Not assessed19 Older33 Could not confirm19 Blogs with no paper11 All blogs13

Paper	Topic	Relevance
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.
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.
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.
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.
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.
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.
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.
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.
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	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	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D latent distillation without multimodal reasoning or language integration.
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.
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.
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	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on sensor noise for depth prediction, not vision-language multimodal models.
GNFormer: Gaussian Neural Field Transformer for Efficient Camera-based Occupancy Prediction The paper introduces a 3D Gaussian neural field transformer for efficient, camera-based occupancy prediction in robotic perception systems. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D occupancy prediction without cross-modal language or multimodal reasoning.
Truncation Samplers Are Nested: Comparing Decoding Rules Is a Measurement Problem The paper presents a theoretical framework using nesting properties to calculate distance bounds and compare language model truncation sampling algorithms efficiently. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Analyzes text generation decoding rules, not multimodal models.
Ellipsoids from Tangents The paper introduces an algorithm that fits multiple ellipsoids in multi-dimensional data by leveraging tangent equations rather than raw points alone. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on mathematical ellipsoid fitting from tangents, not multimodal AI.
Squeeze-Aware-YOLO: Early Channel Recalibration and Multi-Scale Fusion for Real-Time Traffic Sign Detection This paper introduces a lightweight detection framework combining early channel recalibration and multiscale fusion for real-time traffic sign identification. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on standard object detection architectures (YOLO) for vision alone.
Lesion-Aware Attention for Mammography Segmentation with Heterogeneous Supervision This paper introduces a dual-branch framework combining mask-level and image-level supervision for open-vocabulary mammography lesion segmentation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses medical image segmentation under mixed supervision, not multimodal cross-modal modeling.
1Step-WAM: Your World Action Model but Faster using 1-Step Action Generation This paper accelerates world action models by compressing multi-step action denoising into a single forward step parallelized with visual prefilling. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on single-step action denoising in world action models for robotics.
SurgCast: Action-Conditioned Future Skeletons for Controllable Surgical World Models This paper proposes predicting future instrument skeletons from planned actions to guide visually and structurally consistent surgical video generation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on robot action-conditioned surgical video generation rather than multimodal reasoning.
ProtoPur: Prototype-Purity Pseudo-Labeling for Weakly Supervised Instance Learning in Pathology This paper introduces prototype-purity pseudo-labeling to extract accurate instance-level annotations from weakly supervised whole-slide pathology images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on multiple instance learning in pathology images, not multimodal models.
ScenePlacer: Reformulating Scene-Level Object Pose Estimation as Visibility Field Learning This paper proposes estimating 3D object poses within partial scenes by predicting visibility fields in canonical object space. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses 3D shape alignment and point clouds, not cross-modal vision-language reasoning.
Frozen History: When Temporal Losses Stop Accumulation in Learned Real-Time Supersampling This paper demonstrates that accurate registration can cause temporal consistency losses to freeze history accumulation and degrade real-time supersampling accuracy. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on video supersampling and temporal losses, not multimodal reasoning.
Hand2Robot: Object-Centric 4D Hand Reconstruction from Human Demonstrations for Robotics This paper presents a framework to reconstruct 4D hand-object interactions from human demonstration videos to supervise robot manipulation policies. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D/4D pose reconstruction and robotics retargeting rather than multimodal foundation models.
Totem: Object-Centric 3D Memory for World-Consistent Video Generation This paper proposes an object-centric 3D memory framework to maintain persistent object representations and world consistency during video generation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Proposes 3D object-centric memory for video synthesis, not multimodal models.
ChangeT$^3$: Evaluating Vision Test-Time Training for Remote Sensing Change Detection This paper evaluates visual test-time training for remote sensing change detection using a Siamese encoder-decoder architecture with adaptive fast weights. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with bitemporal satellite image change detection without multimodal models.
ML-CLAPPS: A Probabilistic Framework for Imbalanced Multilabel Learning under Class Prioritization This paper introduces a learnable probabilistic instance sampler to handle severe class imbalance and prioritize critical diagnoses in multilabel learning. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Targets multilabel ECG image classification without multimodal reasoning.
Mobility Helps Learning: Unsupervised Model Adaptation for Object Recognition via Movement This paper presents an unsupervised test-time adaptation method that uses movement-induced prediction variance to adapt object recognition models in mobile agents. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses purely on vision test-time adaptation without multimodal elements.
Sharper Frames, Worse Rooms: Viewpoint Coverage Dominates Image Quality in Feed-Forward 3D Reconstruction This paper shows that wide viewpoint coverage produces significantly better 3D room reconstructions than selecting only sharp, motion-free camera frames. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Studies geometric frame selection for 3D reconstruction without multimodal models.
Frequency-Step Cache: Separating Synchronization and Repair for Efficient Autoregressive Video Diffusion This paper introduces a training-free caching method that separates cache synchronization and computation repair to accelerate autoregressive video diffusion generation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Concerns video generation diffusion caching rather than multimodal text-image-video understanding.
Representational Difference Distillation Proposes a knowledge distillation method that focuses learning signals on specific structural disagreements between teacher and student representations. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Applies knowledge distillation to vision classification without multimodal interaction.
Removing the Compute Bottleneck for Event-based Visual Place Recognition with Spiking Neural Networks Implements an aggressively pruned spiking neural network to perform event-based visual place recognition on commodity CPUs in microseconds. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on single-modality event-based sensing rather than multimodal models.
Hybrid Context Forests and Bilateral Viterbi Matching for 3D Rib Centerline Tracing in CT Presents an open-source framework using context forests and Viterbi dynamic programming to extract and number rib centerlines in CT scans. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Exclusively targets 3D medical CT image processing without multimodal reasoning.
From Failure Prediction to Component Selection in Semantic Segmentation Analyzes failure prediction and component selection methods to evaluate which semantic segmentation predictions to retain or inspect. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Studies failure prediction in 2D image semantic segmentation, not multimodal models.
Regime-Aware Router Learning for Multi-Domain Medical Image Generation with Diffusion Experts Evaluates router-learning strategies for combining domain-specialized diffusion experts in multi-domain medical image generation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Involves diffusion image generation rather than cross-modal understanding or VLMs.
ProMoDD: Dataset Distillation for 3D Human Motion via Prototype-Conditioned Diffusion Models Proposes a prototype-conditioned diffusion method to distill large 3D human motion datasets into compact representative subsets. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Studies 3D skeleton action distillation, not multimodal cross-modality models.
All-St3R SLAM: Real-time RGB Dynamic SLAM with Pixel-wise Motion Masking Presents a real-time RGB dynamic SLAM framework that removes moving objects at pixel precision using motion discrepancy analysis. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses geometric dynamic SLAM tracking without multimodal language integration.
Esports World Model Dataset Releases a large gameplay dataset across multiple competitive games to support multi-agent interactive world model research. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Presents a game-engine video and state dataset rather than multimodal foundation models.
VGGA: Geometry-Grounded Autoencoder for Video Generation Proposes a geometry-grounded video autoencoder incorporating structural depth and geometric constraints to improve latent representations for video generation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on latent geometric autoencoders for video generation, not multimodal models.
MFlowHOI: Whole-Body Human-Object Interaction Generation via Part-Aware MeanFlow Presents a one-step framework to generate whole-body human-object interactions efficiently using structured latent spaces. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on motion generation from text and contacts, lacking broader multimodal reasoning.
EgoWholeView: Camera-Only Head-Mounted Capture of Body and Bimanual Hand Motion for Embodied Demonstrations Introduces a six-camera head-mounted system to capture body and bimanual hand motions for embodied demonstrations. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on multi-camera motion capture without multimodal language or reasoning components.
Graph3R: Unifying View Graph Initialization with Feed-Forward Reconstruction Combines view graph initialization with feed-forward reconstruction using a shared geometric representation to handle uncurated multi-scene image collections. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Covers multi-view camera geometry and 3D reconstruction, not multimodal understanding.
FlowAvatar: Real-Time Full-Body Avatars from Sparse Egocentric Inputs on Consumer XR Devices Enables real-time full-body avatar tracking and personalized appearance on standalone consumer headsets using sparse egocentric sensor inputs. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses sensor and camera pose tracking for avatars, not multimodal vision-language models.
DepthTile: Depth-Guided Existing-Image Self-Tiling with Input-Side Tileability Assessment Presents a depth-guided diffusion method to convert images into seamless repeatable tiles while preserving original local geometry and details. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on diffusion-based image tiling using monocular depth, not multimodal reasoning.
ProGAN-Based Synthetic Image Generation for Industrial Visual Inspection of Metallic Parts Applies progressive growing generative adversarial networks to generate synthetic images for industrial defect detection on metallic parts. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on GAN-based synthetic image generation, not multimodal vision-language models.
3D Gaussian Splatting for Fine-grained Urban Scene Reconstruction via Semantic-guided Density Control and Loss Design Uses segmentation guidance to improve density control and loss functions for fine-grained 3D Gaussian Splatting scene reconstruction. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses 3D Gaussian Splatting and segmentation, not cross-modal reasoning models.
ClothAtlas: Joint Garment Identification and State Estimation under Self-Occlusion The paper introduces a flow-matching model that jointly identifies garments and estimates full 3D configurations from partial, occluded point clouds. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D point cloud mesh matching rather than multimodal vision-language models.
RAR: Rate-Adaptive Rollout for Time-Consistent Interactive World Models The paper presents a rate-adaptive rollout framework that allows interactive video world models to operate consistently across varying temporal rates. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses video generation frame rate adaptation rather than cross-modal understanding.
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.
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.
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.
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.
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.
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.
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.
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.

1,081–1,140 of 1,924← Previous Next →