Latest Articles for Fine-tuning

New method enhances reliability of model predictions in real-world applications.

A new approach to integrate diverse cultural insights into language models.

A new method to spark creativity in problem-solving through AI support.

Exploring issues in creating decision-making AI models and solutions.

AV-SUPERB evaluates audio and visual models across various tasks for better performance.

New tools improve how systems retrieve information from long documents.

Exploring how language models reflect personality traits in recruitment.

This study enhances fine-tuning efficiency in neural networks using transductive active learning.

Enhancing Whisper's speech recognition for Vietnamese and other low-resource languages.

A new method for adapting LLMs without extensive labeling.

This article discusses a method to improve LLMs using verbal feedback without overgeneralization.

LoRETTA improves fine-tuning efficiency for large language models with fewer parameters.

Exploring the threats posed by indiscriminate data poisoning in self-supervised learning.

Examining how fine-tuning increases the risk of revealing sensitive training data.

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.