Scientists recommend using more diverse and closer to natural communication data for training, which significantly increases the accuracy of humor recognition.
In experiments with neural networks including RoBERTa, ChatGPT, and Flan-UL2, scientists tested the models’ ability to detect humor in ironic social media messages as well as dialogue in the works of Lewis Carroll, Charles Dickens, and others. Models trained on a variety of data turned out to be more successful at this task.
Source: Ferra
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