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Fine-tuning and aligning question answering models for complex information extraction tasks
The emergence of Large Language Models (LLMs) has boosted performance and possibilities in various NLP tasks.
Combining Deep Learning and Reasoning for Address Detection in Unstructured Text Documents
Extracting information from unstructured text documents is a demanding task, since these documents can have a broad variety of different layouts and a non-trivial reading order, like it is the case for multi-column documents or nested tables.
Evaluation of Representation Models for Text Classification with AutoML Tools
Automated Machine Learning (AutoML) has gained increasing success on tabular data in recent years.
VitrAI -- Applying Explainable AI in the Real World
With recent progress in the field of Explainable Artificial Intelligence (XAI) and increasing use in practice, the need for an evaluation of different XAI methods and their explanation quality in practical usage scenarios arises.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Leveraging Automated Machine Learning for Text Classification: Evaluation of AutoML Tools and Comparison with Human Performance
Recently, Automated Machine Learning (AutoML) has registered increasing success with respect to tabular data.
Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark
In the last few years, Automated Machine Learning (AutoML) has gained much attention.
