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Cognitive Modeling of Semantic Fluency Using Transformers
We report preliminary evidence suggesting that, despite obvious implementational differences in how people and TLMs learn and use language, TLMs can be used to identify individual differences in human fluency task behaviors better than existing computational models, and may offer insights into human memory retrieval strategies -- cognitive process not typically considered to be the kinds of things TLMs can model.
On the Complementarity of Images and Text for the Expression of Emotions in Social Media
The emotions of anger and sadness are best predicted with a multimodal model, while text alone is sufficient for disgust, joy, and surprise.
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