arXiv AI
Jun 3
Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models
arXiv:2606. 02914v1 Announce Type: new Abstract: Background: Oral diseases affect nearly 3.
Computer vision
Detection, segmentation, depth and recognition research, plus the vision backbones that keep displacing the last generation.
arXiv AI
Jun 3
PSViT: A Methodology for Structurally Pruning Spiking Vision Transformers
arXiv:2606. 03257v1 Announce Type: cross Abstract: Spiking Vision Transformer (SViT) models are promising low-power ViT models for solving vision-based tasks with state-of-the-art performance.
arXiv AI
Jun 3
Towards Compact Autonomous Driving Perception with Balanced Learning and Multi-sensor Fusion
arXiv:2606. 02979v1 Announce Type: cross Abstract: We present a novel compact deep multi-task learning model to handle various autonomous driving perception tasks in one forward pass.
arXiv AI
Jun 3
Learned Non-Maximum Suppression for 3D Object Detection
arXiv:2606. 03568v1 Announce Type: cross Abstract: Post-processing is a critical stage in LiDAR-based 3D object detection, where dense and overlapping proposals must be filtered for compact and reliable perception.
arXiv AI
Jun 3
Plan2Map: A Multimodal Benchmark for Document-Grounded Geospatial Boundary Reconstruction from Planning Records
arXiv:2606. 02747v1 Announce Type: cross Abstract: Planning records define restrictions over geographic areas, but their source documents often provide only indirect spatial evidence rather than machine-readable boundaries.
arXiv Machine Learning
Jun 3
GLINT: Sparsely Gated Vision-Language Alignment for Fine-Grained Radiology Representations
arXiv:2606. 03180v1 Announce Type: cross Abstract: Vision-language models (VLMs) for radiology have emerged as a scalable paradigm by leveraging image-report pairs naturally produced in clinical workflows.
arXiv Machine Learning
Jun 3
The Road Ahead in Autonomous Driving: The KITScenes Multimodal Dataset
arXiv:2606. 02956v1 Announce Type: cross Abstract: Existing autonomous driving datasets have enabled major progress, but fall short in sensor fidelity, map completeness, or geographic diversity.
arXiv AI
Jun 3
Forgetting is Not Erasure: Recovering Latent Knowledge via Transport Keys
arXiv:2606. 02860v1 Announce Type: cross Abstract: Catastrophic forgetting is often framed as a representational problem: after sequential training, a model appears to lose the features that supported performance on earlier tasks.
arXiv Machine Learning
Jun 3
RRISE: Robust Radius Inference via a Surrogate Estimator
arXiv:2606. 02876v1 Announce Type: new Abstract: Randomized smoothing (RS) uses a smoothed classifier to provide architecture-agnostic certificates of $\ell_2$ classification robustness, but its dependence on per-input Monte Carlo (MC) sampling undermines its use in real-time systems.
arXiv AI
Jun 3
\textsc{CR-Seg}: Attention-Guided and CoT-Enhanced Coarse-to-Refined Reasoning Segmentation
arXiv:2606. 03564v1 Announce Type: cross Abstract: Reasoning segmentation aims to segment target objects described by complex language through joint visual-textual reasoning.
Hugging Face Trending Papers
Jun 3
HYolo: An Intelligent IoT-Based Object Detection System Using Hypergraph Learning
This paper presents HYolo, an intelligent IoT-based object detection framework that integrates hypergraph learning into the YOLO architecture. Traditional YOLO-based object detection models primarily capture pairwise feature interactions and may fail to model complex high-order relationships among objects and contextual features.
Hugging Face Trending Papers
Jun 2
Graph Regularized Non-negative Reduced Biquaternion Matrix Factorization for Color Image Recognition
Non-negative reduced biquaternion matrix factorization (NRBMF) uses the product of reduced biquaternion (RB) matrices to incorporate the non-negativity constraints of color image pixels into the factorization process. However, NRBMF mainly focuses on reconstruction accuracy and does not exploit the local geometric structure of image data, which may limit the discriminative ability of the learned low-dimensional features.
arXiv AI
Jun 2
Shortcut to Nowhere: Demystifying Deep Spurious Regression
arXiv:2606. 01723v1 Announce Type: cross Abstract: Real-world regression often exhibits shortcuts: attributes that are spuriously correlated with continuous targets in training, yet unreliable under deployment shifts; regressing targets using such shortcuts may fail catastrophically at test time.
arXiv AI
Jun 2
DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle
arXiv:2307. 06647v4 Announce Type: replace-cross Abstract: We propose DeepIPCv2, an end-to-end autonomous driving framework that integrates LiDAR-based environmental perception with command-specific control learning.
arXiv Machine Learning
Jun 2
Iterated Population Based Training with Task-Agnostic Restarts
arXiv:2511. 09190v2 Announce Type: replace Abstract: Hyperparameter Optimization (HPO) can lift the burden of tuning hyperparameters (HPs) of neural networks.
arXiv AI
Jun 2
Ranking vs. Assignment: The Metric Mismatch in Multi-View Object Association
arXiv:2606. 02022v1 Announce Type: cross Abstract: Multi-view object association is an important computer vision problem that underlies many multi-camera perception tasks.
arXiv AI
Jun 2
Flow-Based Generative Modeling for Optimizing Sampling Policies in Compressed Sensing Applications
arXiv:2606. 00078v1 Announce Type: cross Abstract: Numerous modern applications in signal processing and medical imaging necessitate acquiring high-dimensional signals under tight resource constraints.
arXiv AI
Jun 2
Pre-Deployment Robustness Stress Testing for CT Segmentation Systems Using Clinically Motivated Multi-Corruption Augmentation
arXiv:2606. 00491v1 Announce Type: cross Abstract: Deep learning-based CT segmentation systems often achieve high accuracy on clean benchmark images, but their performance may degrade under heterogeneous clinical imaging conditions such as noise, resolution loss, contrast variation, intensity shift, and artifacts.
arXiv AI
Jun 2
An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation
arXiv:2606. 00987v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have shown strong visual understanding and language-guided grounding abilities, yet their capacity for multi-temporal visual reasoning remains underexplored.
arXiv AI
Jun 2
Enhancing Layer Attention Efficiency through Pruning Redundant Retrievals
arXiv:2503. 06473v5 Announce Type: replace-cross Abstract: Growing evidence suggests that layer attention mechanisms, which enhance interaction among layers in deep neural networks, have significantly advanced network architectures.