Latest Articles for Fine-tuning

Leveraging CLIP's visual and text components improves deepfake detection methods.

Examining the sample sizes needed for specialized models to surpass general ones.

This article explores how randomness affects learning with limited labeled data.

Sens-BERT enhances low-cost sensor accuracy for better air quality monitoring.

Enhancing computer understanding of images and text through advanced training techniques.

Introducing Kuaiji, an advanced model tailored for accounting professionals.

A method to enhance language models in responding to unanswerable questions.

Exploring data augmentation techniques and their impact on NLP models.

A new method helps robots learn tasks using simulated data.

A new method combines human video data with robot demonstrations for improved learning.

A novel tool generates diverse visual hallucination instances to improve AI accuracy.

A study on efficient methods for fine-tuning large models through Low-Rank Adaptation.

A new method enhances speech recognition efficiency using low-rank adaptation.

This article examines the dangers of harmful fine-tuning in language models.

Exploring the privacy and security risks linked to Large Language Models.

Researchers enhance Encoder-Decoder models to better predict sentence complexity using linguistic features.

A new method to fine-tune large models with improved efficiency.

Lingo improves DNA analysis through advanced language model techniques.

Model editing can amplify biases and misinformation in language models.

Researchers improve green light production with innovative Kerr microresonators.

A look at RAG and fine-tuning methods for enhancing LLMs' performance on rare topics.

A new method enhances data analysis in high energy physics using self-supervised learning.

TTPXHunter enhances threat intelligence by automating the extraction of TTPs from reports.

ImgTrojan manipulates VLMs using deceptive training data.

A new dataset to assess planning skills of language models in real-life tasks.

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.