Latest Articles for Data Science

Researchers combine data sources to enhance molecular property predictions efficiently.

A fresh approach to fine-tuning models enhances efficiency and accuracy in machine learning tasks.

SLEB streamlines LLMs by removing redundant transformer blocks, enhancing speed and efficiency.

This article discusses a method for learning visual features from video data.

Using RL, data assimilation enhances forecasting accuracy in chaotic environments.

GFlowNets improve sampling accuracy from complex discrete distributions.

A study presents a new model to estimate air pollution levels globally.

A study on reliability and uncertainty in large language models.

This study focuses on improving continual learning methods in 3D semantic tasks.

New methods improve image generation accuracy with multi-concept prompts.

A new way to create simpler models from complex systems for better simulations.

A new approach to evaluate and compare RecSys algorithms using diverse datasets.

A fresh approach to clarify how images influence neural network decisions.

A new framework for generating realistic mobility data using reasoning.

Learn how LinkedIn uses Graph Neural Networks for better user recommendations.

Examining the importance of causal models and interventions in machine learning.

This study investigates how LLMs exhibit value bias in their responses.

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

This article discusses using unlabeled data to improve machine learning models.

A look into how scaling laws shape neural network efficiency and accuracy.

A new method that simplifies graph learning using attention.

A look at how transformers excel with unstructured data in regression tasks.

A new approach improves language models' ability to transform sequences despite limited data.

Introducing ACGCL: a new approach for better graph representation learning.

This article examines a method for assessing uncertainty in network statistics.

New methods improve testing in high-dimensional statistical analysis.

A framework to enhance LLMs' understanding of abstraction.

A study on mixing domain-specific adapters for improved AI performance.

A new method enhances data gathering for better language model alignment.

A new MLP-based model improves accuracy in time series forecasting using random projection layers.

Introducing EP-learning for better treatment effect estimation.

A new method enhances efficiency in graph-based approximate nearest neighbor search.

This article discusses a new method to improve prompt performance for language models.

This method improves analysis of relationships between variables using smaller data samples.

New methods to enhance continuous learning in language models while retaining past knowledge.

Examining performance of language models on financial reasoning tasks.

A study on enhancing language model learning using minimal style changes in training data.

A new approach generates audio captions using only text, improving data efficiency.

A new framework creates customized AI models quickly and easily.

Exploring methods to enhance coding task performance in language models using data.