Saved in:
| Main Authors: | Süalp, Ege, Rezaei, Mina |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.01213 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Mitigating Catastrophic Forgetting in Mathematical Reasoning Finetuning through Mixed Training
by: Reynolds, John Graham
Published: (2025)
by: Reynolds, John Graham
Published: (2025)
Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting
by: Watts, Ishaan, et al.
Published: (2026)
by: Watts, Ishaan, et al.
Published: (2026)
Parameter Alignment Mitigates Catastrophic Forgetting in Multilingual Expert Language Models
by: Ahuja, Sanchit, et al.
Published: (2026)
by: Ahuja, Sanchit, et al.
Published: (2026)
Dynamic Orthogonal Continual Fine-tuning for Mitigating Catastrophic Forgettings
by: Zhang, Zhixin, et al.
Published: (2025)
by: Zhang, Zhixin, et al.
Published: (2025)
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
by: Zhu, Didi, et al.
Published: (2024)
by: Zhu, Didi, et al.
Published: (2024)
CURLoRA: Stable LLM Continual Fine-Tuning and Catastrophic Forgetting Mitigation
by: Fawi, Muhammad
Published: (2024)
by: Fawi, Muhammad
Published: (2024)
Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal
by: Huang, Jianheng, et al.
Published: (2024)
by: Huang, Jianheng, et al.
Published: (2024)
Improved Supervised Fine-Tuning for Large Language Models to Mitigate Catastrophic Forgetting
by: Ding, Fei, et al.
Published: (2025)
by: Ding, Fei, et al.
Published: (2025)
Model-Dowser: Data-Free Importance Probing to Mitigate Catastrophic Forgetting in Multimodal Large Language Models
by: Hwang, Hyeontaek, et al.
Published: (2026)
by: Hwang, Hyeontaek, et al.
Published: (2026)
A Comparative Empirical Study of Catastrophic Forgetting Mitigation in Sequential Task Adaptation for Continual Natural Language Processing Systems
by: Abrahamyan, Aram, et al.
Published: (2026)
by: Abrahamyan, Aram, et al.
Published: (2026)
An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning
by: Luo, Yun, et al.
Published: (2023)
by: Luo, Yun, et al.
Published: (2023)
Locate-then-Merge: Neuron-Level Parameter Fusion for Mitigating Catastrophic Forgetting in Multimodal LLMs
by: Yu, Zeping, et al.
Published: (2025)
by: Yu, Zeping, et al.
Published: (2025)
Conditions for Catastrophic Forgetting in Multilingual Translation
by: Liu, Danni, et al.
Published: (2025)
by: Liu, Danni, et al.
Published: (2025)
Balancing Speciality and Versatility: A Coarse to Fine Framework for Mitigating Catastrophic Forgetting in Large Language Models
by: Zhang, Hengyuan, et al.
Published: (2024)
by: Zhang, Hengyuan, et al.
Published: (2024)
Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates
by: Yamaguchi, Atsuki, et al.
Published: (2025)
by: Yamaguchi, Atsuki, et al.
Published: (2025)
Revisiting Catastrophic Forgetting in Large Language Model Tuning
by: Li, Hongyu, et al.
Published: (2024)
by: Li, Hongyu, et al.
Published: (2024)
Mitigating Catastrophic Forgetting in Multi-domain Chinese Spelling Correction by Multi-stage Knowledge Transfer Framework
by: Xing, Peng, et al.
Published: (2024)
by: Xing, Peng, et al.
Published: (2024)
Analyzing Mitigation Strategies for Catastrophic Forgetting in End-to-End Training of Spoken Language Models
by: Hsiao, Chi-Yuan, et al.
Published: (2025)
by: Hsiao, Chi-Yuan, et al.
Published: (2025)
SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment
by: Huang, Yuqing, et al.
Published: (2025)
by: Huang, Yuqing, et al.
Published: (2025)
Model Editing at Scale leads to Gradual and Catastrophic Forgetting
by: Gupta, Akshat, et al.
Published: (2024)
by: Gupta, Akshat, et al.
Published: (2024)
Understanding Catastrophic Forgetting in Language Models via Implicit Inference
by: Kotha, Suhas, et al.
Published: (2023)
by: Kotha, Suhas, et al.
Published: (2023)
Intelligent Learning Rate Distribution to reduce Catastrophic Forgetting in Transformers
by: Kenneweg, Philip, et al.
Published: (2024)
by: Kenneweg, Philip, et al.
Published: (2024)
Evolutionary Strategies lead to Catastrophic Forgetting in LLMs
by: Abdi, Immanuel, et al.
Published: (2026)
by: Abdi, Immanuel, et al.
Published: (2026)
Catastrophic Forgetting in LLMs: A Comparative Analysis Across Language Tasks
by: Haque, Naimul
Published: (2025)
by: Haque, Naimul
Published: (2025)
Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning
by: Ren, Weijieying, et al.
Published: (2024)
by: Ren, Weijieying, et al.
Published: (2024)
Continual Learning and Catastrophic Forgetting
by: van de Ven, Gido M., et al.
Published: (2024)
by: van de Ven, Gido M., et al.
Published: (2024)
Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning
by: Saggau, Daniel, et al.
Published: (2023)
by: Saggau, Daniel, et al.
Published: (2023)
More Than Catastrophic Forgetting: Integrating General Capabilities For Domain-Specific LLMs
by: Liu, Chengyuan, et al.
Published: (2024)
by: Liu, Chengyuan, et al.
Published: (2024)
Preventing Catastrophic Forgetting: Behavior-Aware Sampling for Safer Language Model Fine-Tuning
by: Pham, Anh, et al.
Published: (2025)
by: Pham, Anh, et al.
Published: (2025)
Mechanistic Analysis of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning
by: Imanov, Olaf Yunus Laitinen
Published: (2026)
by: Imanov, Olaf Yunus Laitinen
Published: (2026)
Can Similarity-Based Domain-Ordering Reduce Catastrophic Forgetting for Intent Recognition?
by: Mannekote, Amogh, et al.
Published: (2024)
by: Mannekote, Amogh, et al.
Published: (2024)
Measuring Catastrophic Forgetting in Cross-Lingual Transfer Paradigms: Exploring Tuning Strategies
by: Koloski, Boshko, et al.
Published: (2023)
by: Koloski, Boshko, et al.
Published: (2023)
Sequencing to Mitigate Catastrophic Forgetting in Continual Learning
by: Moussa, Hesham G., et al.
Published: (2025)
by: Moussa, Hesham G., et al.
Published: (2025)
Speech-IFEval: Evaluating Instruction-Following and Quantifying Catastrophic Forgetting in Speech-Aware Language Models
by: Lu, Ke-Han, et al.
Published: (2025)
by: Lu, Ke-Han, et al.
Published: (2025)
Countering Catastrophic Forgetting of Large Language Models for Better Instruction Following via Weight-Space Model Merging
by: Lyu, Mengxian, et al.
Published: (2026)
by: Lyu, Mengxian, et al.
Published: (2026)
MoE-CT: A Novel Approach For Large Language Models Training With Resistance To Catastrophic Forgetting
by: Li, Tianhao, et al.
Published: (2024)
by: Li, Tianhao, et al.
Published: (2024)
Attractor Patch Networks: Reducing Catastrophic Forgetting with Routed Low-Rank Patch Experts
by: Shashank
Published: (2026)
by: Shashank
Published: (2026)
CORE: Mitigating Catastrophic Forgetting in Continual Learning through Cognitive Replay
by: Zhang, Jianshu, et al.
Published: (2024)
by: Zhang, Jianshu, et al.
Published: (2024)
Mitigating Forgetting Between Supervised and Reinforcement Learning Yields Stronger Reasoners
by: Yuan, Xiangchi, et al.
Published: (2025)
by: Yuan, Xiangchi, et al.
Published: (2025)
Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training
by: Lai, Song, et al.
Published: (2025)
by: Lai, Song, et al.
Published: (2025)
Similar Items
-
Mitigating Catastrophic Forgetting in Mathematical Reasoning Finetuning through Mixed Training
by: Reynolds, John Graham
Published: (2025) -
Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting
by: Watts, Ishaan, et al.
Published: (2026) -
Parameter Alignment Mitigates Catastrophic Forgetting in Multilingual Expert Language Models
by: Ahuja, Sanchit, et al.
Published: (2026) -
Dynamic Orthogonal Continual Fine-tuning for Mitigating Catastrophic Forgettings
by: Zhang, Zhixin, et al.
Published: (2025) -
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
by: Zhu, Didi, et al.
Published: (2024)