arXiv Machine Learning By Xiao Jia

Heterogeneous Neural Predictivity from Language Models During Naturalistic Comprehension

Read the original on arXiv Machine Learning →

arXiv:2606. 26880v1 Announce Type: cross Abstract: Language-model representations provide structured, high-dimensional annotations of naturalistic language stimuli and can serve as informative neural predictors during comprehension.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

arXiv Machine Learning
Aug 21

Decoding silent reading from non-invasive EEG

arXiv:2608. 20186v1 Announce Type: new Abstract: Non-invasive decoding of inner speech faces a fundamental data problem: a corpus pairing brain activity with a person's spontaneous inner monologue cannot be collected, and the available proxy paradigms (cued repetitive and retrospectively reported generative inner speech) are slow to acquire, poorly time-locked, and subject compliance is unverifiable.

By Ingo Marquardt, Anthilia Alchanat, Priyanka Jain