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
NoduleFlow: Automatic 3D Lung Nodule Detection and Segmentation The paper presents a unified deep learning framework for the automatic detection, classification, and segmentation of lung nodules directly from CT scans. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses strictly on 3D CT medical image segmentation without multimodal models.
Dense Endoluminal Mapping and Localisation from Monocular Bronchoscopy The paper introduces a monocular vision system to track bronchoscope tip location and map airway surfaces using standard RGB video alone. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on monocular SLAM without vision-language or multimodal integration.
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.
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	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Concerns specialized biomedical image reconstruction, not multimodal vision-language models.
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.
3D-VITAL: Visibility-aware Identity Training from Artificial Liftings of 3D Reconstruction model for Cross-View Object Re-Identification The paper presents a method using 3D mesh reconstruction and visibility-aware training to improve cross-view object re-identification. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on single-modality 3D reconstruction and ReID, not multimodal models.
The Midas Touch for Metric Depth: Interpretable Metricization for Generalizable Depth Perception The paper introduces a hybrid framework combining explicit depth metricization with data-driven refinement to recover metric depth from relative estimates. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Standard single-modality 3D vision estimation, not multimodal reasoning.
Image Tokenizers Should Be Trained Between Images The paper presents a method that fine-tunes image tokenizers on interpolated latent codes to reduce decoding artifacts in diffusion generation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on vision tokenizers for image generation rather than multimodal reasoning.
Towards Complementary Keypoint Detection via Mixture of Detectors The paper presents a framework that distills multiple keypoint detectors and dynamically routes them per patch for dense image matching. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses purely on geometric vision detectors, not multimodal models.
Carve VFM: Carving Specialists out of Generalists, Automatic Task-Specific Compression of Vision Foundation Models The paper proposes a structured pruning method to compress vision foundation models into compact task-specific models under parameter budgets. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses broadly on vision model pruning rather than multimodal text-image interactions.
A Multi-Task Deep Learning Framework for Pose-Invariant Face Recognition and Facial Landmark Localization The paper presents a dual-branch neural network designed to simultaneously perform pose-invariant face recognition and facial landmark localization. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Standard computer vision task on facial images, not multimodal models.
From Volpiano to Pixels: 30,000 Lines of OMR Ground Truth for Medieval Chant The paper introduces an optical music recognition dataset and pipeline linking medieval chant manuscript images to musical target tokens. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant OMR dataset paper, not general multimodal reasoning or VLMs.
Barycentric Guidance: Turning Foundation Image Editors into Continuous Affective Controllers The paper proposes a training-free guidance method enabling continuous valence-arousal emotional control in foundation image editors. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on text-guided affective image editing, not multimodal understanding.
Mining Cross-Modal Perception Gaps in Autonomous Driving: When Camera and LiDAR Disagree The paper analyzes camera and LiDAR detection discrepancies across driving datasets to evaluate assumptions in multimodal fusion design. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Examines camera-LiDAR sensor fusion for autonomous vehicles.
ConDenseDrive: Knowledge-Dense, Token-Sparse Visual Encoder for End-to-End Autonomous Driving ConDenseDrive combines knowledge distillation and token pruning to create an efficient visual encoder for end-to-end autonomous driving. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on visual encoders for autonomous driving planning.
FOCUS: A Subspecialty Foundation Model for Intraoperative Central Nervous System Pathology FOCUS is a specialized pathology foundation model pretrained on intraoperative frozen-section slides of central nervous system tissue. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on pathology image classification, not multimodal models.
UniMetric: Universal Metric Scale Recovery for Visual Geometry Foundation Models UniMetric provides a training-free framework that recovers metric scale in visual geometry foundation models using object size priors. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses 3D geometric scale recovery rather than multimodal reasoning.
UniLAP: A Unified Latent Action Policy for Cross-Embodiment Manipulation UniLAP introduces a continuous latent action policy trained via flow matching to enable robot manipulation without relying on future frames. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on robotics action representation, not multimodal reasoning models.
Self-Supervised Learning of Semantically Consistent Visual Features via a Simple 3D Prior The paper presents a self-supervised approach using a simple 3D prior to learn semantically consistent visual features for complex objects. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Investigates unimodal self-supervised visual feature correspondence using 3D priors.
MaskSense: Confronting the Visual Exploration Trap in Masked Image Generation MaskSense addresses decoding exploration biases in masked generative models when aligning them with reinforcement learning. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Studies masked generative image models, not multimodal text-vision interaction.
DIME: Scaling Facial Representation Learning via Differential Masked Autoencoding DIME scales facial representation learning using a differential masked autoencoder that supervises differences between identity-matched image pairs. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on vision-only autoencoders for facial representation learning.
PerturbBridge: Direct Phenotypic Supervision for Cellular Perturbation Generation PerturbBridge directly supervises perturbation-specific phenotypes during generative training to model cellular responses in images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Studies biological cellular image generation, not multimodal vision-language models.
A unified three-branch deep learning framework for automated detection and counting of wildlife in aerial imagery The authors present a three-branch deep learning framework for automated aerial wildlife detection, strip delineation, and image matching. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on unimodal aerial computer vision, not multimodal interaction.
Contrastive learning for video reuse detection The paper uses contrastive learning with a Siamese network to extract key visual frames and detect video reuse. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses strictly on video-to-video retrieval, not multimodal text-image models.
MARS: Systematic Multi-Level Acceleration for World Action Models MARS accelerates world action model inference across transformer layers, diffusion denoising, and policy queries without retraining. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Accelerates world action models for robotics, not multimodal understanding.
Multics: Generative Multi-Player World Model with Hierarchical Communication Multics provides a hierarchical communication framework for multi-player interactive video world models to reduce quadratic attention scaling costs. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses multi-player video generation rather than cross-modal reasoning.
DexNinja: Learning Robust Dexterous Cutting Policy with a Real-to-Sim-to-Real Data Engine DexNinja introduces a real-to-sim-to-real framework to train robotic policies for dexterous cutting of deformable objects. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with robotic manipulation, not multimodal vision-language reasoning.
AReA: Adaptive Receptive-Field Attention for Efficient High-Resolution Diffusion Transformers AReA uses an adaptive, coarse-to-fine receptive field attention mechanism to enable efficient high-resolution generation in diffusion transformers. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on attention mechanisms in image diffusion models rather than multimodal reasoning.
HybridDualPathNet: Cross-Fusion Attention of EfficientNetV2 and Swin Transformer for Brain MRI Classification of Alzheimer's and Parkinson's Disease The authors introduce a hybrid architecture combining EfficientNetV2 and Swin Transformer to classify Alzheimer's and Parkinson's disease from brain MRI. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses single-modality medical imaging, not multimodal language models.
HairFlow: Modeling 3D Hair Strands with Multi-Modal Conditioned Diffusion HairFlow generates 3D hair strands using a multimodal diffusion framework conditioned on coarse meshes and multi-view sketches. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Covers conditional 3D mesh generation rather than multimodal reasoning or VLMs.
Brain2Face: A Study on the Relation of EEG Signals and Spatio-temporal Head Avatars The paper presents a dataset and baseline model to track spatio-temporal human head avatars directly from EEG brain signals. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on EEG-to-avatar synthesis rather than multimodal foundation models.
Efficient Fréchet Distributional Decoder Alignment for Latent Generative Models Proposes a post-training decoder alignment method for latent generative models to resolve distribution mismatches between training and generation latents. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses image generation latent decoders rather than multimodal foundation models.
CÆNL: Collapse-Based Active Neural Learning with Objective-Aligned Representation Control Investigates active learning dynamics by regularizing representation collapse and managing sample acquisition across training iterations. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on single-modality vision classification, not multimodal models.
Gaussian Splatting for Real-Time Scene Reconstruction: Methods, Systems, and Trade-offs Surveys real-time 3D Gaussian Splatting scene reconstruction methods, systems, and practical trade-offs across five major technical categories. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Covers 3D novel view synthesis methods rather than multimodal vision-language models.
CrossPortrait: Cross-Species Portrait Animation via Adversarial Motion Alignment Introduces a cross-species portrait animation framework that decomposes motion into head poses and expression keypoints to prevent driving-species leakage. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on video face reenactment rather than multimodal foundation models.
Physical-Field-Bridged Material Parameter Inference from Multi-View Deformation Videos Presents a single-pass framework inferring simulation-ready material parameters from multi-view deformation videos using projected physical response fields. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on vision-based physical parameter estimation, not multimodal language models.
PLEDGE: Progressive Lossy Error-Bounded Compression of 3D Gaussian Splatting Presents an error-bounded progressive compression codec for 3D Gaussian Splatting with user-declared tolerances for primitive distortion. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses 3D Gaussian Splatting compression, not multimodal models.
Background2Background: a self-supervised background removal framework for high dimensional microscopy Introduces a self-supervised background removal framework for high-dimensional microscopy using local pixel shuffling and noise-reduction techniques. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses specialized optical microscopy imaging rather than multimodal language models.
Smartphone-Based, Field-Deployed AI Inspection System for Power Distribution Infrastructure Presents a field-deployed smartphone inspection system combining deep learning and geometry to assess power distribution infrastructure conditions. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Applies standard vision techniques to inspection rather than advancing multimodal foundation models.
From Pixels to Executable Physics: Behavior-Grounded World Models for Embodied Action Consequence Prediction The paper presents a physically consistent world model incorporating robot-terrain contact dynamics to predict quadruped action outcomes from an RGB image. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on video world models for robotics rather than multimodal foundation models.
Calibrated Disambiguation for Partial Multi-label Learning Proposes a calibrated disambiguation model to optimize sample weighting when training classifiers on datasets with noisy or excessive labels. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Standard classification under label noise without multimodal model focus.
Code2Worlds-2: Physically Plausible Agent Harness for Embodied World Simulation Extends dynamic world generation to produce physics-executable simulations with collision meshes and physical dynamics for embodied agents. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on compiling 3D/4D visual scenes into physics simulation formats rather than multimodal model capabilities.
ScenePercept: Scenario-Conditioned Perceptual Assessment of Real-World User-Generated Content Images Introduces an evaluation benchmark to assess user-generated image quality and aesthetics across diverse real-world scenes. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on image quality and aesthetic assessment, not multimodal vision-language reasoning.
Integrating 3D Posture Neutralization with Statistical Shape Modeling for Head-Neck-Shoulder Ergonomic Design Presents a framework integrating posture neutralization with statistical shape modeling to isolate anatomical variations for ergonomic product design. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with 3D scan shape modeling and posture neutralization, not multimodal language models.
SWORD: Scene-Grounded Wasserstein Object-Relation Distance for 3D Scene Graph Prediction Introduces a scene-grounded Wasserstein distance objective to optimize graph-level semantic proximity in 3D scene graph prediction tasks. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with 3D computer vision scene graph prediction rather than multimodal vision-language models.
A Differentiable 3D Scene Graph Metric via Contextual Hellinger Triplet Geometry Proposes a differentiable graph-level loss function to measure semantic and structural discrepancies between predicted 3D scene graphs and ground truth. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Studies 3D scene graph prediction in computer vision, not multimodal language models.
DT-LoRA: Reaching Beyond the Tangent Space of Low-Rank Adaptation Introduces a low-rank adaptation method that splits rank budgets into stable and dynamic branches to capture residual gradients outside the tangent space. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on a general parameter-efficient fine-tuning technique rather than multimodal vision-language models.
AttenIR: Aligning Dense Visual Attention with Mesh Warping for Unsupervised Image Retargeting Proposes an unsupervised image retargeting framework combining dense visual attention with mesh warping to preserve content without manual annotations. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with traditional vision mesh deformation for retargeting, not multimodal language models.
DexStitch: Learning and Composing Dexterous Skills from Human Videos via Contact-Aware Robotic Inpainting Presents a framework that segments long-horizon human manipulation videos into skills and translates them into executable robotic actions. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Studies robotic imitation learning and video inpainting, not multimodal vision-language reasoning.
Beyond the End-Effector: Learning Whole-Arm Contact Manipulation from Human Demonstrations This paper proposes a hierarchical framework for learning whole-arm robot contact manipulation tasks from human demonstrations. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Uses a vision-language model tangentially for constraint generation in a robotics control pipeline.
SPARCL: Spatially Adaptive Regional Coverage for Active Learning in Chest X-ray Analysis This paper introduces an active learning framework balancing uncertainty with submodular spatial coverage for chest X-ray lesion segmentation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals solely with unimodal medical X-ray imaging, not multimodal language or vision-language models.
Frequency Routing and Identity Conditioning for Thermal-to-Visible Face Translation This paper proposes a parameter-efficient framework using frequency-routed adaptation to translate thermal face images into visible-spectrum photographs. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with cross-spectral thermal-visible image translation rather than multimodal language or foundation models.
LoopREG: Representation Supervision Enables Test-Time Recurrent Depth in Diffusion Transformers This paper introduces representation supervision to enable effective test-time recurrent depth scaling in diffusion Transformers. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on recurrent depth in vision transformers without multimodal text-image integration.
HierarchiRetina: A Diabetic Retinopathy Screening and Grading Cascade with Heterogeneous Mixture-of-Experts Lesion Segmentation This paper proposes a multi-stage cascade with heterogeneous mixture-of-experts lesion segmentation for diabetic retinopathy screening and grading. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on clinical eye fundus segmentation without multimodal language-vision capabilities.
PUGS: Physics-Guided Uncertainty Modeling for Underwater Dynamic 3D Gaussian Splatting This paper introduces a physics-guided uncertainty model to improve dynamic 3D Gaussian splatting in turbid underwater environments. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on dynamic 3D Gaussian splatting without multimodal cross-data interaction.
Sea-Net: A Small and Inherently Interpretable Neural Network for Time Series Classification This paper presents a lightweight, interpretable neural network architecture for resource-constrained time-series classification on microcontrollers. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 1D time-series data rather than multimodal vision-language models.
dMRI-F: A Foundation Model for Generalizable Diffusion MRI Analysis from Sparse Acquisitions This paper presents a diffusion MRI foundation model pretrained on masked reconstruction to enable diverse downstream neuroimaging tasks from sparse scans. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on diffusion MRI data reconstruction without multimodal language integration.
Web Scale on a Budget: Tail-Aware Retrieval Evaluation This paper introduces a tail-aware evaluation method that estimates web-scale image retrieval performance using small random distractor samples. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Studies visual instance retrieval scaling laws rather than multimodal language models.
Uncertainty-Aware Semi-Supervised Framework with Supervised Contrastive Learning for Sugarcane Leaf Disease Detection This paper proposes an uncertainty-aware semi-supervised network with supervised contrastive learning to detect sugarcane leaf diseases from limited labeled data. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Applies unimodal computer vision methods without multimodal interaction.

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