Latest Articles for Fine-tuning

Techniques to reduce harmful language generation in AI models.

A method to enhance language models by creating engaging multi-turn dialogues.

A new method to improve model performance on out-of-distribution data.

A novel method to fine-tune language models efficiently with fewer parameters.

This study examines Mix-Training for keyword spotting in noisy speech conditions.

CLIP-CITE enhances CLIP models for specialized tasks while retaining flexibility.

A new method improves image generation using limited datasets effectively.

Improving speech recognition systems for languages with limited online data.

Explore the advantages and applications of Low-Rank Adaptation in AI models.

A new method improves NLP models by focusing on syntactic transformations.

This study focuses on reducing gender bias in AI language models through inclusive language.

Machines improve at answering questions about images through structured training.

This article explores overparameterization and its impact on model training efficiency.

A look into the safety concerns of compressed language models.

SBoRA improves fine-tuning for large language models, saving resources and enhancing performance.

LoRA improves performance of large language models while saving resources.

A new method simplifies personalized image generation from text.

Introducing Group-and-Shuffle matrices for efficient fine-tuning of neural models.

A new method to enhance pre-trained models using selective fine-tuning.

A new framework controls in-context learning to prevent misuse in AI models.

A new method combines video and IMU data to improve action recognition techniques.

A new method enhancing model performance through effective outlier management.

Introducing Random Subspace Adaptation for efficient language model fine-tuning.

A project focused on improving story generation in Arabic using advanced models.

Strategies for improving machine learning models with shifting datasets.

Researchers develop methods to improve language models for various languages.

WeLore brings efficiency to large language models by simplifying weight matrices.

This paper studies how training influences the predictions of large language models.

Study assesses language models' adaptability in summarizing diverse topics.

Discover how transfer learning improves model outcomes using knowledge from related tasks.

A study on how well LLMs function as reliable knowledge bases.

A look at how open-source models measure up against commercial counterparts in biomedical tasks.

Examining issues with large language models in predicting missing list items.

This paper examines backdoor attacks and their implications on machine learning security.

A new method enhances object detection in remote sensing images.

Research enhances language models' ability to process time-related information in tables.

A new method improves how vision-language models adapt during testing.

A new approach to assess model performance and knowledge retention.

This study enhances ultrasound fetal head measurement using deep learning techniques.

A method to improve language model behavior against harmful outputs.