23 citations · 24 across the 4 of their papers we have counts for
4 papers
SYNAPSE: Neuro-Symbolic Visual Thought-to-Text Decoding via Topological Semantic Denoising
Akshaj Murhekar, Abhijit Mishra
Recent advances in large language models have accelerated open-vocabulary EEG-to-imagined-text decoding, where non-invasive neural activity recorded during visual perception is tra…
SENSE: Efficient EEG-to-Text via Privacy-Preserving Semantic Retrieval
Akshaj Murhekar, Christina Liu, Abhijit Mishra +2
Decoding brain activity into natural language is a major challenge in AI with important applications in assistive communication, neurotechnology, and human-computer interaction. Mo…
A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyond
Shreya Shukla, Jose Torres, Akshaj Murhekar +4
Decoding neural activity into human-interpretable representations is a key research direction in brain-computer interfaces (BCIs) and computational neuroscience. Recent progress in…
Thought2Text: Text Generation from EEG Signal using Large Language Models (LLMs)
Abhijit Mishra, Shreya Shukla, Jose Torres +2
Decoding and expressing brain activity in a comprehensible form is a challenging frontier in AI. This paper presents Thought2Text, which uses instruction-tuned Large Language Model…