Fine-tuning Large Language Models for Domain-specific Machine Translation
Fuente:
arXiv
Saved in:
| Main Authors: | Zheng, Jiawei, Hong, Hanghai, Liu, Feiyan, Wang, Xiaoli, Su, Jingsong, Liang, Yonggui, Wu, Shikai |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
EpilepsyLLM: Domain-Specific Large Language Model Fine-tuned with Epilepsy Medical Knowledge
by: Zhao, Xuyang, et al.
Published: (2024)
by: Zhao, Xuyang, et al.
Published: (2024)
EDCO: Dynamic Curriculum Orchestration for Domain-specific Large Language Model Fine-tuning
by: Pang, Jing-Cheng, et al.
Published: (2026)
by: Pang, Jing-Cheng, et al.
Published: (2026)
GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning
by: Tian, Kaiyuan, et al.
Published: (2026)
by: Tian, Kaiyuan, et al.
Published: (2026)
Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective
by: Ghosh, Bishwamittra, et al.
Published: (2026)
by: Ghosh, Bishwamittra, et al.
Published: (2026)
Vaccine: Perturbation-aware Alignment for Large Language Models against Harmful Fine-tuning Attack
by: Huang, Tiansheng, et al.
Published: (2024)
by: Huang, Tiansheng, et al.
Published: (2024)
How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition
by: Dong, Guanting, et al.
Published: (2023)
by: Dong, Guanting, et al.
Published: (2023)
How Multilingual Are Large Language Models Fine-Tuned for Translation?
by: Richburg, Aquia, et al.
Published: (2024)
by: Richburg, Aquia, et al.
Published: (2024)
Selecting Large Language Model to Fine-tune via Rectified Scaling Law
by: Lin, Haowei, et al.
Published: (2024)
by: Lin, Haowei, et al.
Published: (2024)
Exploring Memorization in Fine-tuned Language Models
by: Zeng, Shenglai, et al.
Published: (2023)
by: Zeng, Shenglai, et al.
Published: (2023)
Sparse is Enough in Fine-tuning Pre-trained Large Language Models
by: Song, Weixi, et al.
Published: (2023)
by: Song, Weixi, et al.
Published: (2023)
Private Fine-tuning of Large Language Models with Zeroth-order Optimization
by: Tang, Xinyu, et al.
Published: (2024)
by: Tang, Xinyu, et al.
Published: (2024)
A Fine-tuning Dataset and Benchmark for Large Language Models for Protein Understanding
by: Shen, Yiqing, et al.
Published: (2024)
by: Shen, Yiqing, et al.
Published: (2024)
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
by: Chen, Yukang, et al.
Published: (2023)
by: Chen, Yukang, et al.
Published: (2023)
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)
by: Huang, Wei, et al.
Published: (2025)
Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets
by: Li, Dongyue, et al.
Published: (2025)
by: Li, Dongyue, et al.
Published: (2025)
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models
by: Yin, Haoteng, et al.
Published: (2024)
by: Yin, Haoteng, et al.
Published: (2024)
InstructAV: Instruction Fine-tuning Large Language Models for Authorship Verification
by: Hu, Yujia, et al.
Published: (2024)
by: Hu, Yujia, et al.
Published: (2024)
Fundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models
by: Chen, Pin-Yu, et al.
Published: (2025)
by: Chen, Pin-Yu, et al.
Published: (2025)
Predicting Machine Translation Performance on Low-Resource Languages: The Role of Domain Similarity
by: Khiu, Eric, et al.
Published: (2024)
by: Khiu, Eric, et al.
Published: (2024)
Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models
by: Eiras, Francisco, et al.
Published: (2024)
by: Eiras, Francisco, et al.
Published: (2024)
Efficient End-to-end Language Model Fine-tuning on Graphs
by: Xue, Rui, et al.
Published: (2023)
by: Xue, Rui, et al.
Published: (2023)
Steering Large Language Models for Machine Translation Personalization
by: Scalena, Daniel, et al.
Published: (2025)
by: Scalena, Daniel, et al.
Published: (2025)
Effects of Prompt Length on Domain-specific Tasks for Large Language Models
by: Liu, Qibang, et al.
Published: (2025)
by: Liu, Qibang, et al.
Published: (2025)
Automatic Pruning of Fine-tuning Datasets for Transformer-based Language Models
by: Tayaranian, Mohammadreza, et al.
Published: (2024)
by: Tayaranian, Mohammadreza, et al.
Published: (2024)
Fine-tuning can Help Detect Pretraining Data from Large Language Models
by: Zhang, Hengxiang, et al.
Published: (2024)
by: Zhang, Hengxiang, et al.
Published: (2024)
Prompting and Fine-tuning Large Language Models for Automated Code Review Comment Generation
by: Haider, Md. Asif, et al.
Published: (2024)
by: Haider, Md. Asif, et al.
Published: (2024)
Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
by: Szep, Marton, et al.
Published: (2024)
by: Szep, Marton, et al.
Published: (2024)
Advancing Parameter Efficiency in Fine-tuning via Representation Editing
by: Wu, Muling, et al.
Published: (2024)
by: Wu, Muling, et al.
Published: (2024)
The Impact of Fine-tuning Large Language Models on Automated Program Repair
by: Macháček, Roman, et al.
Published: (2025)
by: Macháček, Roman, et al.
Published: (2025)
Dissecting Fine-Tuning Unlearning in Large Language Models
by: Hong, Yihuai, et al.
Published: (2024)
by: Hong, Yihuai, et al.
Published: (2024)
Information Guided Regularization for Fine-tuning Language Models
by: Sharma, Mandar, et al.
Published: (2024)
by: Sharma, Mandar, et al.
Published: (2024)
Harnessing Large Language Models: Fine-tuned BERT for Detecting Charismatic Leadership Tactics in Natural Language
by: Saeid, Yasser, et al.
Published: (2024)
by: Saeid, Yasser, et al.
Published: (2024)
Virus: Harmful Fine-tuning Attack for Large Language Models Bypassing Guardrail Moderation
by: Huang, Tiansheng, et al.
Published: (2025)
by: Huang, Tiansheng, et al.
Published: (2025)
Memento: Fine-tuning LLM Agents without Fine-tuning LLMs
by: Zhou, Huichi, et al.
Published: (2025)
by: Zhou, Huichi, et al.
Published: (2025)
Fine-tuning Language Models with Generative Adversarial Reward Modelling
by: Yu, Zhang Ze, et al.
Published: (2023)
by: Yu, Zhang Ze, et al.
Published: (2023)
RIFF: Learning to Rephrase Inputs for Few-shot Fine-tuning of Language Models
by: Najafi, Saeed, et al.
Published: (2024)
by: Najafi, Saeed, et al.
Published: (2024)
Fine-tuning Large Language Models for Entity Matching
by: Steiner, Aaron, et al.
Published: (2024)
by: Steiner, Aaron, et al.
Published: (2024)
Layer-wise Importance Matters: Less Memory for Better Performance in Parameter-efficient Fine-tuning of Large Language Models
by: Yao, Kai, et al.
Published: (2024)
by: Yao, Kai, et al.
Published: (2024)
Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration
by: Fu, Wenjie, et al.
Published: (2023)
by: Fu, Wenjie, et al.
Published: (2023)
Simultaneous Masking, Not Prompting Optimization: A Paradigm Shift in Fine-tuning LLMs for Simultaneous Translation
by: Raffel, Matthew, et al.
Published: (2024)
by: Raffel, Matthew, et al.
Published: (2024)
Similar Items
-
EpilepsyLLM: Domain-Specific Large Language Model Fine-tuned with Epilepsy Medical Knowledge
by: Zhao, Xuyang, et al.
Published: (2024) -
EDCO: Dynamic Curriculum Orchestration for Domain-specific Large Language Model Fine-tuning
by: Pang, Jing-Cheng, et al.
Published: (2026) -
GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning
by: Tian, Kaiyuan, et al.
Published: (2026) -
Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective
by: Ghosh, Bishwamittra, et al.
Published: (2026) -
Vaccine: Perturbation-aware Alignment for Large Language Models against Harmful Fine-tuning Attack
by: Huang, Tiansheng, et al.
Published: (2024)