arXiv Machine Learning June 9, 2026 By Lemei Zhang, Peng Liu, Hans Dahle Kvadsheim, August S{\ae}tre Aasv{\ae}r, Shuer Ye, Reza Bonyadi, Maryam Ziaei, Jon Atle Gulla

Decoding Naturalistic Emotion Dynamics from the Brain: An LLM-Enhanced Regression Framework

Read the original on arXiv Machine Learning →

arXiv:2606. 07707v1 Announce Type: new Abstract: Decoding emotional states from neural signals has been typically framed as a discrete, single-label classification task based on emotionally stable stimuli, a formulation that oversimplifies the continuous, fluid, and co-occurring nature of human affect.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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