Removing Timing Shortcuts Improves Non-Invasive Brain-to-Text

arXiv:2609.40359 · cs.LG, q-bio.NC · Submitted 2026-09-30 · Read on arXiv

cs.LG, q-bio.NC

Submitted: 2026-09-30

Updated: 2026-09-30

Code: https://github.com/neural-processing-lab/SimpleB2T

Terminology

• Accuracy — 39× in this paper · explained in 1 episode
• Benchmark — 33× in this paper · explained in 2 episodes
• Core — 16× in this paper · explained in 2 episodes
• Decode — 13× in this paper · explained in 2 episodes
• Embeddings — 13× in this paper · explained in 2 episodes
• Aggregation — 5× in this paper · explained in 1 episode
• Alignment — 4× in this paper · explained in 1 episode
• Generative AI — 4× in this paper · explained in 2 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Adam — 2× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 2× in this paper
• International Conference on Learning Representations — 1× in this paper
• Regularization — 1× in this paper · explained in 3 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• NeuralBench: A Unifying Framework to Benchmark NeuroAI Models
• MEG-XL: Data-Efficient Brain-to-Text via Long-Context Pre-Training
• Unlocking Non-Invasive Brain-to-Text
• The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learning
• A Common Measure of Communication for Speech Brain-Computer Interfaces
• The 2025 PNPL Competition: Speech Detection and Phoneme Classification in the LibriBrain Dataset
• The Semantic Bottleneck: Leveraging Semantic Representations for Non-Invasive Speech Decoding
• HDND: Hierarchical Dynamic Neural Decoding for Multilingual Word/Character Retrieval from Non-Invasive Brain Recordings
• The 2026 PNPL Competition: Word Classification and Efficient Cross-Subject Generalisation in LibriBrain100
• LibriBrain100: One Hundred Hours of Broad and Deep MEG Data for Neural Speech Decoding at Scale
• Qwen3 Technical Report
• Brain-to-Language Decoding: Tasks, Signals, Methods, Evaluation, Practical Use and Beyond
• From Thought to Action: How a Hierarchy of Neural Dynamics Supports Language Production
• LibriBrain: Over 50 Hours of Within-Subject MEG to Improve Speech Decoding Methods at Scale

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