6 papers
The Concept of Representation in ML: Beyond Plato and Aristotle
Gilad Landau, Aviv Keren
Representation is a central concept in modern machine learning, where it usually refers to internal encodings that support learning and generalization. As models scale and their ca…
Elementary, My Dear Watson: Non-Invasive Neural Keyword Spotting in the LibriBrain Dataset
Gereon Elvers, Gilad Landau, Oiwi Parker Jones
Non-invasive brain-computer interfaces (BCIs) are beginning to benefit from large, public benchmarks. However, current benchmarks target relatively simple, foundational tasks like…
The 2025 PNPL Competition: Speech Detection and Phoneme Classification in the LibriBrain Dataset
Gilad Landau, Miran Ãzdogan, Gereon Elvers +15
The advance of speech decoding from non-invasive brain data holds the potential for profound societal impact. Among its most promising applications is the restoration of communicat…
LibriBrain: Over 50 Hours of Within-Subject MEG to Improve Speech Decoding Methods at Scale
Miran Ãzdogan, Gilad Landau, Gereon Elvers +5
LibriBrain represents the largest single-subject MEG dataset to date for speech decoding, with over 50 hours of recordings -- 5 larger than the next comparable dataset and…
The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learning
Dulhan Jayalath, Gilad Landau, Brendan Shillingford +2
The past few years have seen remarkable progress in the decoding of speech from brain activity, primarily driven by large single-subject datasets. However, due to individual variat…
Unlocking Non-Invasive Brain-to-Text
Dulhan Jayalath, Gilad Landau, Oiwi Parker Jones
Despite major advances in surgical brain-to-text (B2T), i.e. transcribing speech from invasive brain recordings, non-invasive alternatives have yet to surpass even chance on standa…