Cover Image

Exploring Open-world Continual Learning with Knowns-Unknowns Knowledge Transfer

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Yujie, Lai, Guannan, Yang, Xin, Li, Yonghao, Bonsangue, Marcello, Li, Tianrui
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving Open-world Continual Learning under the Constraints of Scarce Labeled Data
by: Li, Yujie, et al.
Published: (2025)

Multi-granularity Knowledge Transfer for Continual Reinforcement Learning
by: Pan, Chaofan, et al.
Published: (2024)

Federated Continual Learning via Knowledge Fusion: A Survey
by: Yang, Xin, et al.
Published: (2023)

Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping
by: Lai, Guannan, et al.
Published: (2025)

FedProK: Trustworthy Federated Class-Incremental Learning via Prototypical Feature Knowledge Transfer
by: Gao, Xin, et al.
Published: (2024)

Beyond the Known: Novel Class Discovery for Open-world Graph Learning
by: Jin, Yucheng, et al.
Published: (2024)

A Survey of Continual Reinforcement Learning
by: Pan, Chaofan, et al.
Published: (2025)

Continual Learning for Smart City: A Survey
by: Yang, Li, et al.
Published: (2024)

Personalized Federated Continual Learning via Multi-granularity Prompt
by: Yu, Hao, et al.
Published: (2024)

Known Meets Unknown: Mitigating Overconfidence in Open Set Recognition
by: Zhao, Dongdong, et al.
Published: (2025)

ErrorEraser: Unlearning Data Bias for Improved Continual Learning
by: Cao, Xuemei, et al.
Published: (2025)

Tackling Small Sample Survival Analysis via Transfer Learning: A Study of Colorectal Cancer Prognosis
by: Zhao, Yonghao, et al.
Published: (2025)

Open Continual Feature Selection via Granular-Ball Knowledge Transfer
by: Cao, Xuemei, et al.
Published: (2024)

WST: Weak-to-Strong Knowledge Transfer via Reinforcement Learning
by: Ge, Haosen, et al.
Published: (2025)

Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor
by: Yu, Hao, et al.
Published: (2024)

Low-Complexity Inference in Continual Learning via Compressed Knowledge Transfer
by: Liu, Zhenrong, et al.
Published: (2025)

When a Reinforcement Learning Agent Encounters Unknown Unknowns
by: Zhu, Juntian, et al.
Published: (2025)

A Survey of Route Recommendations: Methods, Applications, and Opportunities
by: Zhang, Shiming, et al.
Published: (2024)

GraphBridge: Towards Arbitrary Transfer Learning in GNNs
by: Ju, Li, et al.
Published: (2025)

Towards Effective Theory of LLMs: A Representation Learning Approach
by: Ustaomeroglu, Muhammed, et al.
Published: (2026)

Out-of-Distribution Generalization in Time Series: A Survey
by: Wu, Xin, et al.
Published: (2025)

Exploratory Machine Learning with Unknown Unknowns
by: Zhao, Peng, et al.
Published: (2020)

MO-EMT-NAS: Multi-Objective Continuous Transfer of Architectural Knowledge Between Tasks from Different Datasets
by: Liao, Peng, et al.
Published: (2024)

Understanding Knowledge Transferability for Transfer Learning: A Survey
by: Wang, Haohua, et al.
Published: (2025)

Use Sparse Autoencoders to Discover Unknown Concepts, Not to Act on Known Concepts
by: Peng, Kenny, et al.
Published: (2025)

CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Community
by: Liu, Yan, et al.
Published: (2024)

Learning to Explore with Lagrangians for Bandits under Unknown Linear Constraints
by: Das, Udvas, et al.
Published: (2024)

Beyond Fixed Variables: Expanding-variate Time Series Forecasting via Flat Scheme and Spatio-temporal Focal Learning
by: Ma, Minbo, et al.
Published: (2025)

Learning Safety Constraints from Demonstrations with Unknown Rewards
by: Lindner, David, et al.
Published: (2023)

Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback
by: Xiong, Guojun, et al.
Published: (2024)

Energy-Structured Low-Rank Adaptation for Continual Learning
by: Li, Longhua, et al.
Published: (2026)

Teach Me to Trick: Exploring Adversarial Transferability via Knowledge Distillation
by: Pradhan, Siddhartha, et al.
Published: (2025)

CMKL: Modality-Aware Continual Learning for Evolving Biomedical Knowledge Graphs
by: Radwan, Yousef A., et al.
Published: (2026)

Open Knowledge Base Canonicalization with Multi-task Learning
by: Liu, Bingchen, et al.
Published: (2024)

Robust Knowledge Transfer in Tiered Reinforcement Learning
by: Huang, Jiawei, et al.
Published: (2023)

Exploration in Knowledge Transfer Utilizing Reinforcement Learning
by: Jedlička, Adam, et al.
Published: (2024)

Hybrid Reward Normalization for Process-supervised Non-verifiable Agentic Tasks
by: Xu, Peiran, et al.
Published: (2025)

Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP
by: Chen, Zixiang, et al.
Published: (2023)

TMLC-Net: Transferable Meta Label Correction for Noisy Label Learning
by: Li, Mengyang
Published: (2025)

Distribution-Level Memory Recall for Continual Learning: Preserving Knowledge and Avoiding Confusion
by: Cheng, Shaoxu, et al.
Published: (2024)