Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance
Fuente:
arXiv
Saved in:
| Main Authors: | Yuan, Bo, Chen, Yulin, Zhang, Yin, Jiang, Wei |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning under Temporal Label Noise
by: Nagaraj, Sujay, et al.
Published: (2024)
by: Nagaraj, Sujay, et al.
Published: (2024)
Robust Deep Hawkes Process under Label Noise of Both Event and Occurrence
by: Tan, Xiaoyu, et al.
Published: (2024)
by: Tan, Xiaoyu, et al.
Published: (2024)
On the Learning Dynamics of Two-layer Linear Networks with Label Noise SGD
by: Zhang, Tongcheng, et al.
Published: (2026)
by: Zhang, Tongcheng, et al.
Published: (2026)
Impact of Label Noise on Learning Complex Features
by: Vashisht, Rahul, et al.
Published: (2024)
by: Vashisht, Rahul, et al.
Published: (2024)
Label Noise Robustness of Conformal Prediction
by: Einbinder, Bat-Sheva, et al.
Published: (2022)
by: Einbinder, Bat-Sheva, et al.
Published: (2022)
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning
by: Ji, Xinyuan, et al.
Published: (2024)
by: Ji, Xinyuan, et al.
Published: (2024)
Exploring Loss Design Techniques For Decision Tree Robustness To Label Noise
by: Sztukiewicz, Lukasz, et al.
Published: (2024)
by: Sztukiewicz, Lukasz, et al.
Published: (2024)
Label Noise Robustness for Domain-Agnostic Fair Corrections via Nearest Neighbors Label Spreading
by: Stromberg, Nathan, et al.
Published: (2024)
by: Stromberg, Nathan, et al.
Published: (2024)
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
by: Cheng, Yao, et al.
Published: (2023)
by: Cheng, Yao, et al.
Published: (2023)
rSDNet: Unified Robust Neural Learning against Label Noise and Adversarial Attacks
by: Jana, Suryasis, et al.
Published: (2026)
by: Jana, Suryasis, et al.
Published: (2026)
SAP: Corrective Machine Unlearning with Scaled Activation Projection for Label Noise Robustness
by: Kodge, Sangamesh, et al.
Published: (2024)
by: Kodge, Sangamesh, et al.
Published: (2024)
Handling Label Noise via Instance-Level Difficulty Modeling and Dynamic Optimization
by: Zhang, Kuan, et al.
Published: (2025)
by: Zhang, Kuan, et al.
Published: (2025)
FANoise: Singular Value-Adaptive Noise Modulation for Robust Multimodal Representation Learning
by: Li, Jiaoyang, et al.
Published: (2025)
by: Li, Jiaoyang, et al.
Published: (2025)
Seeking Physics in Diffusion Noise
by: Tang, Chujun, et al.
Published: (2026)
by: Tang, Chujun, et al.
Published: (2026)
DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection
by: Chen, Qingfeng, et al.
Published: (2025)
by: Chen, Qingfeng, et al.
Published: (2025)
A Conformal Prediction Score that is Robust to Label Noise
by: Penso, Coby, et al.
Published: (2024)
by: Penso, Coby, et al.
Published: (2024)
Balancing Accuracy, Calibration, and Efficiency in Active Learning with Vision Transformers Under Label Noise
by: Mots'oehli, Moseli, et al.
Published: (2025)
by: Mots'oehli, Moseli, et al.
Published: (2025)
Noise-Robustness Through Noise: A Framework combining Asymmetric LoRA with Poisoning MoE
by: Wang, Zhaokun, et al.
Published: (2025)
by: Wang, Zhaokun, et al.
Published: (2025)
NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity Recognition
by: Merdjanovska, Elena, et al.
Published: (2024)
by: Merdjanovska, Elena, et al.
Published: (2024)
Hide and Find: A Distributed Adversarial Attack on Federated Graph Learning
by: Liu, Jinshan, et al.
Published: (2026)
by: Liu, Jinshan, et al.
Published: (2026)
Distantly-Supervised Joint Extraction with Noise-Robust Learning
by: Li, Yufei, et al.
Published: (2023)
by: Li, Yufei, et al.
Published: (2023)
Harnessing the Power of Beta Scoring in Deep Active Learning for Multi-Label Text Classification
by: Tan, Wei, et al.
Published: (2024)
by: Tan, Wei, et al.
Published: (2024)
GCI-ViTAL: Gradual Confidence Improvement with Vision Transformers for Active Learning on Label Noise
by: Mots'oehli, Moseli, et al.
Published: (2024)
by: Mots'oehli, Moseli, et al.
Published: (2024)
Policy Filtration for RLHF to Mitigate Noise in Reward Models
by: Zhang, Chuheng, et al.
Published: (2024)
by: Zhang, Chuheng, et al.
Published: (2024)
Improving Noise Robustness through Abstractions and its Impact on Machine Learning
by: Ibias, Alfredo, et al.
Published: (2024)
by: Ibias, Alfredo, et al.
Published: (2024)
Learning to Explore with Parameter-Space Noise: A Deep Dive into Parameter-Space Noise for Reinforcement Learning with Verifiable Rewards
by: Bai, Bizhe, et al.
Published: (2026)
by: Bai, Bizhe, et al.
Published: (2026)
The Malignant Tail: Spectral Segregation of Label Noise in Over-Parameterized Networks
by: Wang, Zice
Published: (2026)
by: Wang, Zice
Published: (2026)
Drift-aware Collaborative Assistance Mixture of Experts for Heterogeneous Multistream Learning
by: Yu, En, et al.
Published: (2025)
by: Yu, En, et al.
Published: (2025)
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
by: Liu, Shuze Daniel, et al.
Published: (2024)
by: Liu, Shuze Daniel, et al.
Published: (2024)
Contrastive Learning with Nasty Noise
by: Zhao, Ziruo
Published: (2025)
by: Zhao, Ziruo
Published: (2025)
Beyond Noisy-TVs: Noise-Robust Exploration Via Learning Progress Monitoring
by: Hou, Zhibo, et al.
Published: (2025)
by: Hou, Zhibo, et al.
Published: (2025)
Robust Federated Learning Over the Air: Combating Heavy-Tailed Noise with Median Anchored Clipping
by: Li, Jiaxing, et al.
Published: (2024)
by: Li, Jiaxing, et al.
Published: (2024)
When Noisy Labels Meet Class Imbalance on Graphs: A Graph Augmentation Method with LLM and Pseudo Label
by: Xia, Riting, et al.
Published: (2025)
by: Xia, Riting, et al.
Published: (2025)
NoiseAR: AutoRegressing Initial Noise Prior for Diffusion Models
by: Li, Zeming, et al.
Published: (2025)
by: Li, Zeming, et al.
Published: (2025)
Meta-Learning Guided Label Noise Distillation for Robust Signal Modulation Classification
by: Hao, Xiaoyang, et al.
Published: (2024)
by: Hao, Xiaoyang, et al.
Published: (2024)
Hide in Plain Sight: Clean-Label Backdoor for Auditing Membership Inference
by: Chen, Depeng, et al.
Published: (2024)
by: Chen, Depeng, et al.
Published: (2024)
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
by: Chen, Hao, et al.
Published: (2023)
by: Chen, Hao, et al.
Published: (2023)
Quantum Tunneling-Aware Machine Learning: Physics-Derived Noise Models for Robust Deployment
by: Hwang, Uiwon, et al.
Published: (2026)
by: Hwang, Uiwon, et al.
Published: (2026)
NoiseFormer -- Noise Diffused Symmetric Attention Transformer
by: Kumar, Phani, et al.
Published: (2026)
by: Kumar, Phani, et al.
Published: (2026)
Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization
by: Wang, Dongwei, et al.
Published: (2024)
by: Wang, Dongwei, et al.
Published: (2024)
Similar Items
-
Learning under Temporal Label Noise
by: Nagaraj, Sujay, et al.
Published: (2024) -
Robust Deep Hawkes Process under Label Noise of Both Event and Occurrence
by: Tan, Xiaoyu, et al.
Published: (2024) -
On the Learning Dynamics of Two-layer Linear Networks with Label Noise SGD
by: Zhang, Tongcheng, et al.
Published: (2026) -
Impact of Label Noise on Learning Complex Features
by: Vashisht, Rahul, et al.
Published: (2024) -
Label Noise Robustness of Conformal Prediction
by: Einbinder, Bat-Sheva, et al.
Published: (2022)