Latest Articles for Fine-tuning

This article discusses new methods for improving few-shot learning performance.

A look at how computing power and algorithms have transformed language models.

Examining how noise in pre-training data impacts model performance.

New methods enhance image quality while preserving individual identity.

LoRA+ enhances model performance through tailored learning rates in deep learning.

Exploring new privacy concerns in the use of diffusion models.

Investigating model compression methods to improve efficiency and defenses against attacks.

A novel method for improving image quality during AI testing.

Learn how model reprogramming enhances machine learning without heavy adjustments.

This method enhances StyleGAN's efficiency while preserving image variety.

A new method for enhancing diffusion models while keeping diversity in generated outputs.

Learn how to adjust LLMs for unique business needs through fine tuning.

A new method enhances language models' understanding of medical terms.

This study evaluates various language models for text classification using minimal training data.

Learn about language models, hallucination, and ways to improve accuracy.

Focusing on LayerNorm improves fine-tuning efficiency for BERT models.

Leveraging NLP to efficiently extract information from lengthy legal judgments.

FT2Ra enhances code completion efficiency through retrieval methods without full model retraining.

Exploring how benign data can unintentionally produce harmful outputs in language models.

This article discusses the role of few-shot learning in speeding up drug discovery.

Innovative techniques for improving TTS models and reducing knowledge loss.

A new method enhances on-device models for efficient AI function calling.

New methods improve model performance in unsupervised learning tasks.

CodecNeRF improves 3D representations with fast encoding and high-quality images.

This article discusses enhancing machine translation quality using language models and feedback.

A study on enhancing few-shot learning through effective backbone training techniques.

Research focuses on enhancing LLMs for better Ukrainian representation.

Research highlights strategies to enhance SAM for medical imaging tasks.

An overview of prompting and prefix-tuning in transformer models.

Enhancing QA systems through fine-tuning and reasoning for better finance insights.

Exploring how transformer models enhance molecular property predictions across various fields.

A new method to fine-tune models while ensuring data privacy.

A new method enhances multimodal models using shared visual prompts.

Examining how stance detection reveals public opinions on social media.

Exploring innovative methods for improving written communication accuracy.

An assessment of how well LLMs remember factual information and the factors involved.

Researchers improve AI models using synthetic images for effective classification.

A study on adapting LLMs for efficient clinical note generation.

Small language models can enhance reasoning through self-generated critiques.

A study on detecting conspiracy theories in German-language Telegram messages.