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Add arXiv citation (DOI 2605.22893); reword Task 1 to 'silent meditation'

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  1. README.md +10 -12
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@@ -117,7 +117,7 @@ Per-channel z-score normalisation is applied at run time by the dataset loader,
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  | Task | Goal | Input segments | N | Evaluation |
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  |---|---|---|---|---|
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- | **Task 1** — Cognitive State Decoding | Resting (`restCE01`) vs. focused meditation (`slMedita`) | pre-intervention only | 74 | intra-subject (block-wise / chronological), inter-subject 5-fold, LOSO |
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  | **Task 2** — Technique Classification | HK vs. SA vs. BF from `slMedita` (and/or `Medita`) | pre and post separately | 74 (pre) / 44 (post) | inter-subject 5-fold |
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  | **Task 3** — Cross-Session Adaptation | Pre-trained Task-1 models applied to post-intervention `slMedita` vs. `restCE01` | post-intervention | 44 | zero-shot and N-shot (10/30) calibration; intra-subject |
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@@ -223,21 +223,19 @@ This dataset is released under **CC BY-NC 4.0**. You may copy, redistribute, rem
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  ## Citation
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- > *Citation information (arXiv link and DOI) will be added in a future update. In the meantime, please cite this Hugging Face repository directly (`L-FAME-Dataset-Benchmark/L-FAME`).*
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-
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- <!--
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- Citation block held back until arXiv link / DOI are available.
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  ```bibtex
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- @inproceedings{lfame2026,
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- title = {L-FAME: Longitudinal Focused Attention Meditation EEG Dataset and Benchmark},
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- author = {<TODO: fill in author list at acceptance>},
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- booktitle = {<TODO: fill in venue / arXiv ref upon release>},
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- year = {2026},
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- note = {Preprint}
 
 
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  }
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  ```
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- -->
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  ## Authors and acknowledgments
 
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  | Task | Goal | Input segments | N | Evaluation |
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  |---|---|---|---|---|
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+ | **Task 1** — Cognitive State Decoding | Resting (`restCE01`) vs. silent meditation (`slMedita`) | pre-intervention only | 74 | intra-subject (block-wise / chronological), inter-subject 5-fold, LOSO |
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  | **Task 2** — Technique Classification | HK vs. SA vs. BF from `slMedita` (and/or `Medita`) | pre and post separately | 74 (pre) / 44 (post) | inter-subject 5-fold |
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  | **Task 3** — Cross-Session Adaptation | Pre-trained Task-1 models applied to post-intervention `slMedita` vs. `restCE01` | post-intervention | 44 | zero-shot and N-shot (10/30) calibration; intra-subject |
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  ## Citation
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+ If you use this dataset or benchmark, please cite:
 
 
 
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  ```bibtex
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+ @misc{li2026lfamelongitudinalfocusedattention,
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+ title={L-FAME: Longitudinal Focused Attention Meditation EEG Dataset and Benchmark},
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+ author={Angqi Li and Ab Basit Rafi Syed and Hamzeh Alzweri and Taosheng Liu and Barry H. Cohen and Saiprasad Ravishankar},
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+ year={2026},
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+ eprint={2605.22893},
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+ archivePrefix={arXiv},
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+ primaryClass={eess.SP},
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+ url={https://arxiv.org/abs/2605.22893},
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  }
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  ```
 
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  ## Authors and acknowledgments