Optimizing Language Models for Grammatical Acceptability: A Comparative Study of Fine-Tuning Techniques
Fuente:
arXiv
Saved in:
| Main Authors: | Ratan, Shobhit, Knight, Farley, Jerfel, Ghada, Ho, Sze Chung |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
How to Make the Most of LLMs' Grammatical Knowledge for Acceptability Judgments
by: Ide, Yusuke, et al.
Published: (2024)
by: Ide, Yusuke, et al.
Published: (2024)
Explain-then-Process: Using Grammar Prompting to Enhance Grammatical Acceptability Judgments
by: Scheinberg, Russell, et al.
Published: (2025)
by: Scheinberg, Russell, et al.
Published: (2025)
Optimizing Medical Question-Answering Systems: A Comparative Study of Fine-Tuned and Zero-Shot Large Language Models with RAG Framework
by: Hassan, Tasnimul, et al.
Published: (2025)
by: Hassan, Tasnimul, et al.
Published: (2025)
Fine-tuning Language Models for Recipe Generation: A Comparative Analysis and Benchmark Study
by: Vij, Anneketh, et al.
Published: (2025)
by: Vij, Anneketh, et al.
Published: (2025)
Parameter-Efficient Fine-Tuning for Medical Text Summarization: A Comparative Study of Lora, Prompt Tuning, and Full Fine-Tuning
by: Shernazarov, Ulugbek, et al.
Published: (2026)
by: Shernazarov, Ulugbek, et al.
Published: (2026)
Model Fusion through Bayesian Optimization in Language Model Fine-Tuning
by: Jang, Chaeyun, et al.
Published: (2024)
by: Jang, Chaeyun, et al.
Published: (2024)
How to Tune a Multilingual Encoder Model for Germanic Languages: A Study of PEFT, Full Fine-Tuning, and Language Adapters
by: Oji, Romina, et al.
Published: (2025)
by: Oji, Romina, et al.
Published: (2025)
Fine Tuning Large Language Models for Medicine: The Role and Importance of Direct Preference Optimization
by: Savage, Thomas, et al.
Published: (2024)
by: Savage, Thomas, et al.
Published: (2024)
Dynamic Adaptive Optimization for Effective Sentiment Analysis Fine-Tuning on Large Language Models
by: Ding, Hongcheng, et al.
Published: (2024)
by: Ding, Hongcheng, et al.
Published: (2024)
Overtrained Language Models Are Harder to Fine-Tune
by: Springer, Jacob Mitchell, et al.
Published: (2025)
by: Springer, Jacob Mitchell, et al.
Published: (2025)
Memorization in Fine-Tuned Large Language Models
by: Savine, Danil
Published: (2025)
by: Savine, Danil
Published: (2025)
ClaimIQ at CheckThat! 2025: Comparing Prompted and Fine-Tuned Language Models for Verifying Numerical Claims
by: Anik, Anirban Saha, et al.
Published: (2025)
by: Anik, Anirban Saha, et al.
Published: (2025)
A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning
by: Peng, Cheng, et al.
Published: (2025)
by: Peng, Cheng, et al.
Published: (2025)
Natural Language Fine-Tuning
by: Liu, Jia, et al.
Published: (2024)
by: Liu, Jia, et al.
Published: (2024)
Safety-Aware Fine-Tuning of Large Language Models
by: Choi, Hyeong Kyu, et al.
Published: (2024)
by: Choi, Hyeong Kyu, et al.
Published: (2024)
Phased Instruction Fine-Tuning for Large Language Models
by: Pang, Wei, et al.
Published: (2024)
by: Pang, Wei, et al.
Published: (2024)
Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models
by: Barnett, Scott, et al.
Published: (2024)
by: Barnett, Scott, et al.
Published: (2024)
Detecting AI-Generated Paraphrases in Bengali: A Comparative Study of Zero-Shot and Fine-Tuned Transformers
by: Islam, Md. Rakibul, et al.
Published: (2025)
by: Islam, Md. Rakibul, et al.
Published: (2025)
Large Language Model-Driven Dynamic Assessment of Grammatical Accuracy in English Language Learner Writing
by: Jaganov, Timur, et al.
Published: (2025)
by: Jaganov, Timur, et al.
Published: (2025)
A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals
by: Cadeddu, Andrea, et al.
Published: (2025)
by: Cadeddu, Andrea, et al.
Published: (2025)
Reversing Large Language Models for Efficient Training and Fine-Tuning
by: Gal, Eshed, et al.
Published: (2025)
by: Gal, Eshed, et al.
Published: (2025)
Impact of Fine-Tuning Methods on Memorization in Large Language Models
by: Hou, Jie, et al.
Published: (2025)
by: Hou, Jie, et al.
Published: (2025)
Fine-Tuned Language Models for Domain-Specific Summarization and Tagging
by: Wang, Jun, et al.
Published: (2025)
by: Wang, Jun, et al.
Published: (2025)
Comparative Analysis of Efficient Adapter-Based Fine-Tuning of State-of-the-Art Transformer Models
by: Siddiqui, Saad Mashkoor, et al.
Published: (2025)
by: Siddiqui, Saad Mashkoor, et al.
Published: (2025)
Supervised Fine-Tuning versus Reinforcement Learning: A Study of Post-Training Methods for Large Language Models
by: Jiang, Haitao, et al.
Published: (2026)
by: Jiang, Haitao, et al.
Published: (2026)
Learning to Prioritize IT Tickets: A Comparative Evaluation of Embedding-based Approaches and Fine-Tuned Transformer Models
by: LÊ, Minh Tri, et al.
Published: (2025)
by: LÊ, Minh Tri, et al.
Published: (2025)
A Comparative Analysis of Instruction Fine-Tuning LLMs for Financial Text Classification
by: Fatemi, Sorouralsadat, et al.
Published: (2024)
by: Fatemi, Sorouralsadat, et al.
Published: (2024)
Noise Augmented Fine Tuning for Mitigating Hallucinations in Large Language Models
by: Khadangi, Afshin, et al.
Published: (2025)
by: Khadangi, Afshin, et al.
Published: (2025)
KnowTuning: Knowledge-aware Fine-tuning for Large Language Models
by: Lyu, Yougang, et al.
Published: (2024)
by: Lyu, Yougang, et al.
Published: (2024)
Refining Salience-Aware Sparse Fine-Tuning Strategies for Language Models
by: Liu, Xinxin, et al.
Published: (2024)
by: Liu, Xinxin, et al.
Published: (2024)
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
by: Zheng, Yaowei, et al.
Published: (2024)
by: Zheng, Yaowei, et al.
Published: (2024)
Efficient Fine-Tuning of Large Language Models for Automated Medical Documentation
by: Leong, Hui Yi, et al.
Published: (2024)
by: Leong, Hui Yi, et al.
Published: (2024)
Scaling Data Diversity for Fine-Tuning Language Models in Human Alignment
by: Song, Feifan, et al.
Published: (2024)
by: Song, Feifan, et al.
Published: (2024)
Comparing LLM and Fine-Tuned Model Performance on NVDRS Circumstance Extraction with Varying Prompt Complexity
by: Martin, Geoffrey, et al.
Published: (2026)
by: Martin, Geoffrey, et al.
Published: (2026)
MedBioLM: Optimizing Medical and Biological QA with Fine-Tuned Large Language Models and Retrieval-Augmented Generation
by: Kim, Seonok
Published: (2025)
by: Kim, Seonok
Published: (2025)
Is Crowdsourcing Breaking Your Bank? Cost-Effective Fine-Tuning of Pre-trained Language Models with Proximal Policy Optimization
by: Yang, Shuo, et al.
Published: (2024)
by: Yang, Shuo, et al.
Published: (2024)
Parameter-Efficient Fine-Tuning for Low-Resource Languages: A Comparative Study of LLMs for Bengali Hate Speech Detection
by: Islam, Akif, et al.
Published: (2025)
by: Islam, Akif, et al.
Published: (2025)
Should We Fine-Tune or RAG? Evaluating Different Techniques to Adapt LLMs for Dialogue
by: Alghisi, Simone, et al.
Published: (2024)
by: Alghisi, Simone, et al.
Published: (2024)
DSGram: Dynamic Weighting Sub-Metrics for Grammatical Error Correction in the Era of Large Language Models
by: Xie, Jinxiang, et al.
Published: (2024)
by: Xie, Jinxiang, et al.
Published: (2024)
You Only Fine-tune Once: Many-Shot In-Context Fine-Tuning for Large Language Models
by: He, Wenchong, et al.
Published: (2025)
by: He, Wenchong, et al.
Published: (2025)
Similar Items
-
How to Make the Most of LLMs' Grammatical Knowledge for Acceptability Judgments
by: Ide, Yusuke, et al.
Published: (2024) -
Explain-then-Process: Using Grammar Prompting to Enhance Grammatical Acceptability Judgments
by: Scheinberg, Russell, et al.
Published: (2025) -
Optimizing Medical Question-Answering Systems: A Comparative Study of Fine-Tuned and Zero-Shot Large Language Models with RAG Framework
by: Hassan, Tasnimul, et al.
Published: (2025) -
Fine-tuning Language Models for Recipe Generation: A Comparative Analysis and Benchmark Study
by: Vij, Anneketh, et al.
Published: (2025) -
Parameter-Efficient Fine-Tuning for Medical Text Summarization: A Comparative Study of Lora, Prompt Tuning, and Full Fine-Tuning
by: Shernazarov, Ulugbek, et al.
Published: (2026)