1 citations · 1 across the 4 of their papers we have counts for
3 papers · 1 filter
A cross-species neural foundation model for end-to-end speech decoding
Yizi Zhang, Linyang He, Chaofei Fan +9
Speech brain-computer interfaces (BCIs) aim to restore communication for people with paralysis by translating neural activity into text. Most systems use cascaded frameworks that d…
Shrinking the Generation-Verification Gap with Weak Verifiers
Jon Saad-Falcon, E. Kelly Buchanan, Mayee F. Chen +10
Verifiers can improve language model capabilities by scoring and ranking responses from generated candidates. Currently, high-quality verifiers are either unscalable (e.g., humans)…
Brain-to-Text Benchmark '24: Lessons Learned
Francis R. Willett, Jingyuan Li, Trung Le +13
Speech brain-computer interfaces aim to decipher what a person is trying to say from neural activity alone, restoring communication to people with paralysis who have lost the abili…