Cover Image

LoD: Loss-difference OOD Detection by Intentionally Label-Noisifying Unlabeled Wild Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Geng, Chuanxing, Li, Qifei, Wang, Xinrui, Liang, Dong, Chen, Songcan, Yuen, Pong C.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dynamic Against Dynamic: An Open-set Self-learning Framework
by: Yang, Haifeng, et al.
Published: (2024)

Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends
by: Wang, Xinrui, et al.
Published: (2023)

Explicit View-labels Matter: A Multifacet Complementarity Study of Multi-view Clustering
by: Geng, Chuanxing, et al.
Published: (2022)

Filter, Obstruct and Dilute: Defending Against Backdoor Attacks on Semi-Supervised Learning
by: Wang, Xinrui, et al.
Published: (2025)

Forgetting, Ignorance or Myopia: Revisiting Key Challenges in Online Continual Learning
by: Wang, Xinrui, et al.
Published: (2024)

Pushing One Pair of Labels Apart Each Time in Multi-Label Learning: From Single Positive to Full Labels
by: Li, Xiang, et al.
Published: (2023)

All-around Neural Collapse for Imbalanced Classification
by: Zhang, Enhao, et al.
Published: (2024)

Texture2LoD3: Enabling LoD3 Building Reconstruction With Panoramic Images
by: Tang, Wenzhao, et al.
Published: (2025)

Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey
by: Li, Chaohua, et al.
Published: (2025)

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning
by: Wang, Xinrui, et al.
Published: (2025)

Online Continual Learning with Dynamic Label Hierarchies
by: Wang, Xinrui, et al.
Published: (2026)

ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning
by: Zhang, Enhao, et al.
Published: (2025)

Global Pre-fixing, Local Adjusting: A Simple yet Effective Contrastive Strategy for Continual Learning
by: Tang, Jia, et al.
Published: (2025)

No Regularization is Needed: An Efficient and Effective Model for Incomplete Label Distribution Learning
by: Li, Xiang, et al.
Published: (2023)

A Survey on Incomplete Multi-label Learning: Recent Advances and Future Trends
by: Li, Xiang, et al.
Published: (2024)

MLS2LoD3: Refining low LoDs building models with MLS point clouds to reconstruct semantic LoD3 building models
by: Wysocki, Olaf, et al.
Published: (2024)

A LoD of Gaussians: Unified Training and Rendering for Ultra-Large Scale Reconstruction with External Memory
by: Windisch, Felix, et al.
Published: (2025)

Adaptive Federated Minimax Optimization with Lower Complexities
by: Huang, Feihu, et al.
Published: (2022)

LoD-Loc: Aerial Visual Localization using LoD 3D Map with Neural Wireframe Alignment
by: Zhu, Juelin, et al.
Published: (2024)

Beyond Dense States: Elevating Sparse Transcoders to Active Operators for Latent Reasoning
by: Wang, Yadong, et al.
Published: (2026)

CM2LoD3: Reconstructing LoD3 Building Models Using Semantic Conflict Maps
by: Hanke, Franz, et al.
Published: (2025)

LoD-Structured 3D Gaussian Splatting for Streaming Video Reconstruction
by: Liu, Xinhui, et al.
Published: (2026)

Unlocking the Power of Open Set : A New Perspective for Open-Set Noisy Label Learning
by: Wan, Wenhai, et al.
Published: (2023)

M-Loss: Quantifying Model Merging Compatibility with Limited Unlabeled Data
by: Wang, Tiantong, et al.
Published: (2026)

Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data
by: Takahashi, Hiroshi, et al.
Published: (2024)

Negative Label Guided OOD Detection with Pretrained Vision-Language Models
by: Jiang, Xue, et al.
Published: (2024)

FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients
by: Qiu, Xinchi, et al.
Published: (2024)

Filling holes in LoD2 building models
by: Gao, Weixiao, et al.
Published: (2024)

Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization
by: Huang, Feihu, et al.
Published: (2023)

GLIP-OOD: Zero-Shot Graph OOD Detection with Graph Foundation Model
by: Xu, Haoyan, et al.
Published: (2025)

Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data
by: Mishra, Aayush, et al.
Published: (2025)

MetaOOD: Automatic Selection of OOD Detection Models
by: Qin, Yuehan, et al.
Published: (2024)

InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning
by: Huang, Zhe, et al.
Published: (2024)

NegRefine: Refining Negative Label-Based Zero-Shot OOD Detection
by: Ansari, Amirhossein, et al.
Published: (2025)

Integrating Distribution Matching into Semi-Supervised Contrastive Learning for Labeled and Unlabeled Data
by: Nakayama, Shogo, et al.
Published: (2026)

Tuning Out-of-Distribution (OOD) Detectors Without Given OOD Data
by: Mondal, Sudeepta, et al.
Published: (2026)

Topology Reorganized Graph Contrastive Learning with Mitigating Semantic Drift
by: Zhang, Jiaqiang, et al.
Published: (2024)

Federated Unlearning Model Recovery in Data with Skewed Label Distributions
by: Yu, Xinrui, et al.
Published: (2024)

A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label Learning
by: Li, Xiang, et al.
Published: (2020)

On Leveraging Unlabeled Data for Concurrent Positive-Unlabeled Classification and Robust Generation
by: Yu, Bing, et al.
Published: (2020)