:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Huang, Wei, Cheng, Anda, Wang, Yinggui
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2509.08255
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Mitigating Catastrophic Forgetting in Language Transfer via Model Merging
by: Alexandrov, Anton, et al.
Published: (2024)

Information Leakage from Embedding in Large Language Models
by: Wan, Zhipeng, et al.
Published: (2024)

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

Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting
by: Watts, Ishaan, et al.
Published: (2026)

A Fast, Performant, Secure Distributed Training Framework For Large Language Model
by: Huang, Wei, et al.
Published: (2024)

DPF-CM: A Data Processing Framework with Privacy-Preserving Vector Databases for Chinese Medical LLMs Training and Deployment
by: Huang, Wei, et al.
Published: (2025)

Analyzing Mitigation Strategies for Catastrophic Forgetting in End-to-End Training of Spoken Language Models
by: Hsiao, Chi-Yuan, et al.
Published: (2025)

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

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

MEGA: Second-Order Gradient Alignment for Catastrophic Forgetting Mitigation in GFSCIL
by: Pang, Jinhui, et al.
Published: (2025)

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

Predicting the Susceptibility of Examples to Catastrophic Forgetting
by: Hacohen, Guy, et al.
Published: (2024)

Mitigating Catastrophic Forgetting with Adaptive Transformer Block Expansion in Federated Fine-Tuning
by: Huo, Yujia, et al.
Published: (2025)

LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning
by: Huang, Wei, et al.
Published: (2026)

Understanding Catastrophic Forgetting in Language Models via Implicit Inference
by: Kotha, Suhas, et al.
Published: (2023)

Mitigating Catastrophic Forgetting in Mathematical Reasoning Finetuning through Mixed Training
by: Reynolds, John Graham
Published: (2025)

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

Are Time Series Foundation Models Susceptible to Catastrophic Forgetting?
by: Karaouli, Nouha, et al.
Published: (2025)

Catastrophic Forgetting Mitigation via Discrepancy-Weighted Experience Replay
by: Xu, Xinrun, et al.
Published: (2025)

Fine-Grained Gradient Restriction: A Simple Approach for Mitigating Catastrophic Forgetting
by: Liu, Bo, et al.
Published: (2024)

Robust Policy Optimization to Prevent Catastrophic Forgetting
by: Sabbaghi, Mahdi, et al.
Published: (2026)

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

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

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

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

FlexFed: Mitigating Catastrophic Forgetting in Heterogeneous Federated Learning in Pervasive Computing Environments
by: Alosaime, Sara, et al.
Published: (2025)

An Efficient Rehearsal Scheme for Catastrophic Forgetting Mitigation during Multi-stage Fine-tuning
by: Bai, Andrew, et al.
Published: (2024)

Avoid Catastrophic Forgetting with Rank-1 Fisher from Diffusion Models
by: Wang, Zekun, et al.
Published: (2025)

Eidetic Learning: an Efficient and Provable Solution to Catastrophic Forgetting
by: Dronen, Nicholas, et al.
Published: (2025)

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

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

Multi-Head Attention as a Source of Catastrophic Forgetting in MoE Transformers
by: Chen, Anrui, et al.
Published: (2026)

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

The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting -- An Analytical Model
by: Goldfarb, Daniel, et al.
Published: (2024)

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression
by: Huang, Wei, et al.
Published: (2025)

Holographic Knowledge Manifolds: A Novel Pipeline for Continual Learning Without Catastrophic Forgetting in Large Language Models
by: Arndt, Justin
Published: (2025)

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

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

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

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