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README.md

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+---
+license: mit
+pretty_name: L-Mind
+size_categories:
+- 10K<n<100K
+
+task_categories:
+- image-to-image
+
+language:
+- en
+- zh
+
+tags:
+- eeg
+- fnirs
+- bci
+- image-editing
+- multimodal
+
+configs:
+- config_name: speech
+  data_files:
+  - split: train
+    path: train_speech.jsonl
+  - split: test
+    path: test_speech.jsonl
+
+- config_name: legacy
+  data_files:
+  - split: train
+    path: train_0424.jsonl
+  - split: test
+    path: test_0424.jsonl
+---
+
+# L-Mind: A Multimodal Dataset for Neural-Driven Image Editing
+
+This dataset is part of the **NeurIPS 2025** paper: **"Neural-Driven Image Editing"**, which introduces **LoongX**, a hands-free image editing approach driven by multimodal neurophysiological signals.
+
+## 📄 Overview
+**L-Mind** is a large-scale multimodal dataset designed to bridge Brain-Computer Interfaces (BCIs) with generative AI. It enables research into accessible, intuitive image editing for individuals with limited motor control or language abilities.
+
+- **Total Samples:** 23,928 image editing pairs
+- **Participants:** 12 subjects (plus cross-subject evaluation data)
+- **Task:** Instruction-based image editing viewed and conceived by users
+
+## 🧠 Modalities
+The dataset features synchronized recordings of:
+1.  **EEG** (Electroencephalography): Captures rapid neural dynamics (4 channels: Pz, Fp2, Fpz, Oz).
+2.  **fNIRS** (Functional Near-Infrared Spectroscopy): Measures hemodynamic responses (cognitive load/emotion).
+3.  **PPG** (Photoplethysmography): Monitors physiological state (heart rate/stress).
+4.  **Head Motion**: 6-axis IMU data tracking user movement.
+5.  **Speech**: Audio instructions provided by users.
+6.  **Visuals**: Source Image, Target Image, and Text Instruction.
+
+## 🚀 Applications
+This dataset supports the training of neural-driven generative models (like LoongX) that can interpret user intent directly from brain and physiological signals to perform:
+- Background replacement
+- Object manipulation
+- Global stylistic changes
+- Text editing
+
+## 🔗 Resources
+- **Project Website:** [https://loongx1.github.io](https://loongx1.github.io)
+- **Paper:** [Neural-Driven Image Editing](https://arxiv.org/abs/2507.05397)
+
+## 📚 Citation
+If you use this dataset, please cite:
+```bibtex
+@inproceedings{zhouneural,
+  title={Neural-Driven Image Editing},
+  author={Zhou, Pengfei and Xia, Jie and Peng, Xiaopeng and Zhao, Wangbo and Ye, Zilong and Li, Zekai and Yang, Suorong and Pan, Jiadong and Chen, Yuanxiang and Wang, Ziqiao and others},
+  booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems}
+}
+```