Add model card for LiVeAction

README.md

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+---
+pipeline_tag: image-to-image
+---
+
+# LiVeAction: Lightweight, Versatile, and Asymmetric Codec Design for Real-time Operation
+
+LiVeAction is a neural codec architecture designed for real-time operation on resource-constrained devices, such as wearable sensors or remote sensing platforms. It addresses the limitations of generative neural codecs by using an FFT-inspired encoder structure to reduce computational complexity and a variance-based rate penalty to enable efficient training across arbitrary signal modalities.
+
+- **Paper:** [LiVeAction: a Lightweight, Versatile, and Asymmetric Neural Codec Design for Real-time Operation](https://huggingface.co/papers/2605.06628)
+- **Project Page:** [https://ut-sysml.github.io/liveaction](https://ut-sysml.github.io/liveaction)
+- **Code:** [https://github.com/UT-SysML/liveaction](https://github.com/UT-SysML/liveaction)
+- **Library:** [livecodec](https://pypi.org/project/livecodec) (`pip install livecodec`)
+
+## Citation
+
+```bibtex
+@inproceedings{jacobellis2026liveaction,
+  title={LiVeAction: Lightweight, Versatile, and Asymmetric Codec Design for Real-time Operation},
+  author={Jacobellis, Dan and Yadwadkar, Neeraja J.},
+  booktitle={IEEE Data Compression Conference (DCC)},
+  year={2026},
+  url={https://ut-sysml.github.io/liveaction}
+}
+```