Copertina

How to Leverage Predictive Uncertainty Estimates for Reducing Catastrophic Forgetting in Online Continual Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Serra, Giuseppe, Werner, Ben, Buettner, Florian
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond
di: Serra, Giuseppe, et al.
Pubblicazione: (2024)

Sequencing to Mitigate Catastrophic Forgetting in Continual Learning
di: Moussa, Hesham G., et al.
Pubblicazione: (2025)

Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning
di: Elsayed, Mohamed, et al.
Pubblicazione: (2024)

On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
di: Peng, Ze, et al.
Pubblicazione: (2025)

Continual Learning and Catastrophic Forgetting
di: van de Ven, Gido M., et al.
Pubblicazione: (2024)

CORE: Mitigating Catastrophic Forgetting in Continual Learning through Cognitive Replay
di: Zhang, Jianshu, et al.
Pubblicazione: (2024)

Revisiting Catastrophic Forgetting in Continual Knowledge Graph Embedding
di: Pons, Gerard, et al.
Pubblicazione: (2026)

Improving Perturbation-based Explanations by Understanding the Role of Uncertainty Calibration
di: Decker, Thomas, et al.
Pubblicazione: (2025)

Why Uncertainty Calibration Matters for Reliable Perturbation-based Explanations
di: Decker, Thomas, et al.
Pubblicazione: (2025)

Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning
di: Ren, Weijieying, et al.
Pubblicazione: (2024)

A Conformal Predictive Measure for Assessing Catastrophic Forgetting
di: Pitsiorlas, Ioannis, et al.
Pubblicazione: (2025)

From Entropy to Calibrated Uncertainty: Training Language Models to Reason About Uncertainty
di: Jenane, Azza, et al.
Pubblicazione: (2026)

Can LLMs Alleviate Catastrophic Forgetting in Graph Continual Learning? A Systematic Study
di: Cheng, Ziyang, et al.
Pubblicazione: (2025)

Catastrophic Forgetting in Kolmogorov-Arnold Networks
di: Rahman, Mohammad Marufur, et al.
Pubblicazione: (2025)

Continual Deep Reinforcement Learning to Prevent Catastrophic Forgetting in Jamming Mitigation
di: Davaslioglu, Kemal, et al.
Pubblicazione: (2024)

Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning
di: Jiang, Gangwei, et al.
Pubblicazione: (2025)

DATS: Distance-Aware Temperature Scaling for Calibrated Class-Incremental Learning
di: Serra, Giuseppe, et al.
Pubblicazione: (2025)

Mind the Gap: A Framework for Assessing Pitfalls in Multimodal Active Learning
di: Eisenhardt, Dustin, et al.
Pubblicazione: (2026)

Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention
di: Koebler, Alexander, et al.
Pubblicazione: (2025)

Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems
di: Banerjee, Sourasekhar, et al.
Pubblicazione: (2026)

CURLoRA: Stable LLM Continual Fine-Tuning and Catastrophic Forgetting Mitigation
di: Fawi, Muhammad
Pubblicazione: (2024)

TFGN: Task-Free, Replay-Free Continual Pre-Training Without Catastrophic Forgetting at LLM Scale
di: Ganguli, Anurup
Pubblicazione: (2026)

Intelligent Learning Rate Distribution to reduce Catastrophic Forgetting in Transformers
di: Kenneweg, Philip, et al.
Pubblicazione: (2024)

Explaining Robustness to Catastrophic Forgetting Through Incremental Concept Formation
di: Barari, Nicki, et al.
Pubblicazione: (2025)

Catastrophic Forgetting Mitigation Through Plateau Phase Activity Profiling
di: Mashiach, Idan, et al.
Pubblicazione: (2025)

Non-Contrastive Vision-Language Learning with Predictive Embedding Alignment
di: Kuhn, Lukas, et al.
Pubblicazione: (2026)

Avoiding Catastrophe in Online Learning by Asking for Help
di: Plaut, Benjamin, et al.
Pubblicazione: (2024)

Evolutionary Strategies lead to Catastrophic Forgetting in LLMs
di: Abdi, Immanuel, et al.
Pubblicazione: (2026)

Overcoming Catastrophic Forgetting by Exemplar Selection in Task-oriented Dialogue System
di: Chen, Chen, et al.
Pubblicazione: (2024)

Forget Forgetting: Continual Learning in a World of Abundant Memory
di: Cho, Dongkyu, et al.
Pubblicazione: (2025)

Gradient Correlation Subspace Learning against Catastrophic Forgetting
di: Dubnov, Tammuz, et al.
Pubblicazione: (2024)

Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning
di: Dou, Xuhui, et al.
Pubblicazione: (2026)

A Methodology-Oriented Study of Catastrophic Forgetting in Incremental Deep Neural Networks
di: Kumar, Ashutosh, et al.
Pubblicazione: (2024)

Overcoming Catastrophic Forgetting in Tabular Data Classification: A Pseudorehearsal-based approach
di: García-Santaclara, Pablo, et al.
Pubblicazione: (2024)

Dynamic Orthogonal Continual Fine-tuning for Mitigating Catastrophic Forgettings
di: Zhang, Zhixin, et al.
Pubblicazione: (2025)

BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning
di: Liu, Yi, et al.
Pubblicazione: (2024)

Accurate Forgetting for Heterogeneous Federated Continual Learning
di: Wuerkaixi, Abudukelimu, et al.
Pubblicazione: (2025)

SNAP: Stopping Catastrophic Forgetting in Hebbian Learning with Sigmoidal Neuronal Adaptive Plasticity
di: Xu, Tianyi, et al.
Pubblicazione: (2024)

Context Channel Capacity: An Information-Theoretic Framework for Understanding Catastrophic Forgetting
di: Cheng, Ran
Pubblicazione: (2026)

Surgical Knowledge Rewrite in Compact LLMs: An 'Unlearn-then-Learn' Strategy with ($IA^3$) for Localized Factual Modulation and Catastrophic Forgetting Mitigation
di: Ngugi, Stanley
Pubblicazione: (2025)