Is EEG-to-Text Feasible in Real-World Scenarios? An In-Depth Analysis Using a Neuropsychology-Inspired Benchmark

Zihan Zhang; Yu Bao; Xiao Ding; Tianyi Jiang; Kai Xiong

doi:10.18653/v1/2026.acl-long.61

2026

ACL main Long PapersCo-first author (listed first)共一第一

Is EEG-to-Text Feasible in Real-World Scenarios? An In-Depth Analysis Using a Neuropsychology-Inspired BenchmarkEEG到文本能否走向真实场景？基于神经心理学启发基准的深入分析

Zihan Zhang, Yu Bao, Xiao Ding^*, Tianyi Jiang, Kai Xiong

Corresponding author通讯作者

Brain–computer interfaces脑机接口Language & cognition语言与认知

Research overview研究介绍

A neuropsychology-inspired benchmark for examining EEG-to-text decoding and its evaluation in realistic settings.以神经心理学启发的基准考察EEG到文本解码，关注真实使用场景下的评估问题。

Publication details发表信息

Venue期刊／会议: ACL main Long Papers
Year年份: 2026
DOI: 10.18653/v1/2026.acl-long.61
Publication type成果类型: Conference paper会议论文

Paper论文 Code代码

Citation引用

@inproceedings{zhang2026eeg,
  title = {Is EEG-to-Text Feasible in Real-World Scenarios? An In-Depth Analysis Using a Neuropsychology-Inspired Benchmark},
  author = {Zhang, Zihan and Bao, Yu and Ding, Xiao and Jiang, Tianyi and Xiong, Kai},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  pages = {1378--1393},
  year = {2026},
  doi = {10.18653/v1/2026.acl-long.61}
}