Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
Benchmarking four compact LLMs on a Raspberry Pi 500+ shows that smaller models such as TinyLlama are far more practical for local edge workloads, while reasoning-focused models trade latency for ...
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