EEG-Based Brain-LLM Interface for Human Preference Aligned Generation
Large language models (LLMs) are becoming an increasingly important component of human--computer interaction, enabling users to coordinate a wide range of intelligent agents through natural language. While language-based interfaces are powerful and flexible, they implicitly assume that users can reliably produce explicit linguistic input, an assumption that may not hold for users with speech or motor impairments, e.g., Amyotrophic Lateral Sclerosis (ALS). In this work, we investigate whether neural signals can be used as an alternative input to LLMs, particularly to support those socially marginalized or underserved users. We build a simple brain-LLM interface, which uses EEG signals to g...
| Authors | Junzi Zhang, Jianing Shen, Weijie Tu et al. |
|---|---|
| Primary category | eess.SP |
| Published | 3 March 2026 |
| Last updated at source | 3 March 2026 |
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