arXiv:2603.24356v1 Announce Type: new
Abstract: We derive a Riemannian metric on three-dimensional color space from the Fisher information of neural population codes in the visual pathway. Photoreceptor adaptation, retinal opponent channels, and cortical population encoding each map onto a geometric construction, producing a metric tensor whose components correspond to measurable neural quantities. The resulting 17-parameter model is fitted jointly to four independent threshold datasets: MacAdam’s (1942) chromaticity ellipses, the Koenderink et al. (2026) three-dimensional ellipsoids, Wright’s (1941) wavelength discrimination function, and the Huang et al. (2012) threshold color difference ellipses, covering 96 independently measured discrimination conditions across varied chromaticities and luminances. The joint fit achieves STRESS of 23.9 on MacAdam, 20.8 on Koenderink et al., 30.1 on Wright, and 30.8 on Huang et al.
Depression subtype classification from social media posts: few-shot prompting vs. fine-tuning of large language models
BackgroundSocial media provides timely proxy signals of mental health, but reliable tweet-level classification of depression subtypes remains challenging due to short, noisy text, overlapping symptomatology,