Evaluating Multimodal Large Language Models (MLLMs) in text-rich scenarios is crucial, given their increasing versatility. However, current benchmarks mainly assess general visual comprehension, overlooking the nuanced challenges of text-rich content. MLLMs like...

Computer vision, machine learning, and data analysis across many fields have all seen a surge in the usage of synthetic data in the past few years. Synthetic means to mimic complicated situations that would be challenging, if not impossible, to record in the actual...

Language models based on the transformers are pivotal in advancing the field of AI. Traditionally, these models have been deployed to interpret and generate human language by predicting token sequences, a fundamental process in their operational framework. Given their...

In computational linguistics, much research focuses on how language models handle and interpret extensive textual data. These models are crucial for tasks that require identifying and extracting specific information from large volumes of text, presenting a...

As businesses increasingly rely on data-driven decision-making, the ability to extract insights and derive value from data has become quite essential. Acquiring skills in data science enables professionals to unlock new opportunities for innovation and gain a...

A group of researchers in France introduced Dr.Benchmark to address the need for the evaluation of masked language models in French, particularly in the biomedical domain. There have been significant advances in the field of NLP, particularly in pre-trained language...