Advanced models like CNNs , LSTMs, and Transformers are frequently tested on this dataset.
While there is no single academic paper titled exactly "jada-imdb," the query most likely refers to the foundational paper that introduced the for sentiment analysis, which is the most cited work associated with this data. Foundational IMDb Dataset Paper jada-imdb
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. Advanced models like CNNs , LSTMs, and Transformers
This paper introduced a dataset of , specifically balanced with 25,000 positive and 25,000 negative samples. It has since become the benchmark for testing various machine learning and deep learning models, including: Maas, Raymond E
International Conference on Machine Learning (ICML), 2011. Dataset Details
The original paper that established the large-scale IMDb movie review dataset used widely in Natural Language Processing (NLP) is: Learning Word Vectors for Sentiment Analysis
Often used as a baseline for binary classification performance.