:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hwang, Hyeontaek, Son, Nguyen Dinh, Kim, Daeyoung
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2602.04509
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
by: Zhu, Didi, et al.
Published: (2024)

Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal
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)

Parameter Alignment Mitigates Catastrophic Forgetting in Multilingual Expert Language Models
by: Ahuja, Sanchit, et al.
Published: (2026)

Revisiting Catastrophic Forgetting in Large Language Model Tuning
by: Li, Hongyu, et al.
Published: (2024)

Mitigating Catastrophic Forgetting in Continual Learning through Model Growth
by: Süalp, Ege, 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)

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

Locate-then-Merge: Neuron-Level Parameter Fusion for Mitigating Catastrophic Forgetting in Multimodal LLMs
by: Yu, Zeping, et al.
Published: (2025)

TB-AVA: Text as a Semantic Bridge for Audio-Visual Parameter Efficient Finetuning
by: Kim, Seongah, 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)

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

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

Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates
by: Yamaguchi, Atsuki, 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)

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

MoE-CT: A Novel Approach For Large Language Models Training With Resistance To Catastrophic Forgetting
by: Li, Tianhao, et al.
Published: (2024)

Reference-Based Post-OCR Processing with LLM for Precise Diacritic Text in Historical Document Recognition
by: Do, Thao, et al.
Published: (2024)

Towards Comprehensive Vietnamese Retrieval-Augmented Generation and Large Language Models
by: Duc, Nguyen Quang, et al.
Published: (2024)

Conditions for Catastrophic Forgetting in Multilingual Translation
by: Liu, Danni, et al.
Published: (2025)

Model Editing at Scale leads to Gradual and Catastrophic Forgetting
by: Gupta, Akshat, et al.
Published: (2024)

VARCO-VISION: Expanding Frontiers in Korean Vision-Language Models
by: Ju, Jeongho, et al.
Published: (2024)

Preventing Catastrophic Forgetting: Behavior-Aware Sampling for Safer Language Model Fine-Tuning
by: Pham, Anh, et al.
Published: (2025)

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

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)

MEMETRON: Metaheuristic Mechanisms for Test-time Response Optimization of Large Language Models
by: Nguyen, Son The, et al.
Published: (2025)

LooComp: Leverage Leave-One-Out Strategy to Encoder-only Transformer for Efficient Query-aware Context Compression
by: Do, Thao, et al.
Published: (2026)

Catastrophic Forgetting in LLMs: A Comparative Analysis Across Language Tasks
by: Haque, Naimul
Published: (2025)

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

CURATRON: Complete and Robust Preference Data for Rigorous Alignment of Large Language Models
by: Nguyen, Son The, 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)

Speech-IFEval: Evaluating Instruction-Following and Quantifying Catastrophic Forgetting in Speech-Aware Language Models
by: Lu, Ke-Han, et al.
Published: (2025)

Prefixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization
by: Son, Seungwoo, et al.
Published: (2024)

Mechanistic Analysis of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning
by: Imanov, Olaf Yunus Laitinen
Published: (2026)

SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment
by: Huang, Yuqing, et al.
Published: (2025)

Counterfactual Probing for Hallucination Detection and Mitigation in Large Language Models
by: Feng, Yijun
Published: (2025)

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

BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models
by: Chang, Yupeng, et al.
Published: (2024)

Exploring Forgetting in Large Language Model Pre-Training
by: Liao, Chonghua, et al.
Published: (2024)

Synthetic Data Generation for Phrase Break Prediction with Large Language Model
by: Lee, Hoyeon, et al.
Published: (2025)