:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Hengyuan, Wu, Yanru, Li, Dawei, Yang, Sak, Zhao, Rui, Jiang, Yong, Tan, Fei
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language
Accès en ligne:	https://arxiv.org/abs/2404.10306
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Improved Supervised Fine-Tuning for Large Language Models to Mitigate Catastrophic Forgetting
par: Ding, Fei, et autres
Publié: (2025)

Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
par: Zhu, Didi, et autres
Publié: (2024)

Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal
par: Huang, Jianheng, et autres
Publié: (2024)

An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning
par: Luo, Yun, et autres
Publié: (2023)

Parameter Alignment Mitigates Catastrophic Forgetting in Multilingual Expert Language Models
par: Ahuja, Sanchit, et autres
Publié: (2026)

Dynamic Orthogonal Continual Fine-tuning for Mitigating Catastrophic Forgettings
par: Zhang, Zhixin, et autres
Publié: (2025)

Model-Dowser: Data-Free Importance Probing to Mitigate Catastrophic Forgetting in Multimodal Large Language Models
par: Hwang, Hyeontaek, et autres
Publié: (2026)

Revisiting Catastrophic Forgetting in Large Language Model Tuning
par: Li, Hongyu, et autres
Publié: (2024)

Mitigating Catastrophic Forgetting in Continual Learning through Model Growth
par: Süalp, Ege, et autres
Publié: (2025)

Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting
par: Watts, Ishaan, et autres
Publié: (2026)

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

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

Preventing Catastrophic Forgetting: Behavior-Aware Sampling for Safer Language Model Fine-Tuning
par: Pham, Anh, et autres
Publié: (2025)

Analyzing Mitigation Strategies for Catastrophic Forgetting in End-to-End Training of Spoken Language Models
par: Hsiao, Chi-Yuan, et autres
Publié: (2025)

Mitigating Catastrophic Forgetting in Multi-domain Chinese Spelling Correction by Multi-stage Knowledge Transfer Framework
par: Xing, Peng, et autres
Publié: (2024)

Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates
par: Yamaguchi, Atsuki, et autres
Publié: (2025)

More Than Catastrophic Forgetting: Integrating General Capabilities For Domain-Specific LLMs
par: Liu, Chengyuan, et autres
Publié: (2024)

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

Understanding Catastrophic Forgetting in Language Models via Implicit Inference
par: Kotha, Suhas, et autres
Publié: (2023)

EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models
par: Xing, Shangyu, et autres
Publié: (2024)

MoE-CT: A Novel Approach For Large Language Models Training With Resistance To Catastrophic Forgetting
par: Li, Tianhao, et autres
Publié: (2024)

Countering Catastrophic Forgetting of Large Language Models for Better Instruction Following via Weight-Space Model Merging
par: Lyu, Mengxian, et autres
Publié: (2026)

Mitigating Catastrophic Forgetting in Large Language Models with Forgetting-aware Pruning
par: Huang, Wei, et autres
Publié: (2025)

Survey of Specialized Large Language Model
par: Yang, Chenghan, et autres
Publié: (2025)

Locate-then-Merge: Neuron-Level Parameter Fusion for Mitigating Catastrophic Forgetting in Multimodal LLMs
par: Yu, Zeping, et autres
Publié: (2025)

Conditions for Catastrophic Forgetting in Multilingual Translation
par: Liu, Danni, et autres
Publié: (2025)

Mitigating Forgetting in LLM Fine-Tuning via Low-Perplexity Token Learning
par: Wu, Chao-Chung, et autres
Publié: (2025)

Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training
par: Lai, Song, et autres
Publié: (2025)

SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment
par: Huang, Yuqing, et autres
Publié: (2025)

A Comparative Empirical Study of Catastrophic Forgetting Mitigation in Sequential Task Adaptation for Continual Natural Language Processing Systems
par: Abrahamyan, Aram, et autres
Publié: (2026)

Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models
par: Lv, Qitan, et autres
Publié: (2024)

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

Towards Coarse-to-Fine Evaluation of Inference Efficiency for Large Language Models
par: Chen, Yushuo, et autres
Publié: (2024)

Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning
par: Ren, Weijieying, et autres
Publié: (2024)

Dynamic Expert Specialization: Towards Catastrophic Forgetting-Free Multi-Domain MoE Adaptation
par: Li, Junzhuo, et autres
Publié: (2025)

Model Editing at Scale leads to Gradual and Catastrophic Forgetting
par: Gupta, Akshat, et autres
Publié: (2024)

BPO: Towards Balanced Preference Optimization between Knowledge Breadth and Depth in Alignment
par: Wang, Sizhe, et autres
Publié: (2024)

BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models
par: Chang, Yupeng, et autres
Publié: (2024)

Mitigating Reversal Curse in Large Language Models via Semantic-aware Permutation Training
par: Guo, Qingyan, et autres
Publié: (2024)

Evolutionary Strategies lead to Catastrophic Forgetting in LLMs
par: Abdi, Immanuel, et autres
Publié: (2026)