🔥[BitNet v2] Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs (#144)

Author: DefTruth

README.md

@@ -241,6 +241,7 @@ python3 download_pdfs.py # The code is generated by Doubao AI
 |2024.08|🔥[ACTIVATION SPARSITY] TRAINING-FREE ACTIVATION SPARSITY IN LARGE LANGUAGE MODELS(@MIT etc)|[[pdf]](https://arxiv.org/pdf/2408.14690)|[[TEAL]](https://github.com/FasterDecoding/TEAL) ![](https://img.shields.io/github/stars/FasterDecoding/TEAL.svg?style=social)|⭐️ |
 |2024.09|🔥[VPTQ] VPTQ: EXTREME LOW-BIT VECTOR POST-TRAINING QUANTIZATION FOR LARGE LANGUAGE MODELS(@Microsoft)|[[pdf]](https://arxiv.org/pdf/2409.17066)|[[VPTQ]](https://github.com/microsoft/VPTQ) ![](https://img.shields.io/github/stars/microsoft/VPTQ.svg?style=social)|⭐️ |
 |2024.11|🔥[BitNet] BitNet a4.8: 4-bit Activations for 1-bit LLMs(@Microsoft)|[[pdf]](https://arxiv.org/pdf/2411.04965)|[[bitnet]](https://github.com/microsoft/unilm/tree/master/bitnet) ![](https://img.shields.io/github/stars/microsoft/unilm.svg?style=social)|⭐️ |
+|2025.04|🔥[**BitNet v2**] BitNet v2: Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs(@Microsoft)|[[pdf]](https://arxiv.org/pdf/2504.18415)|[[bitnet]](https://github.com/microsoft/unilm/tree/master/bitnet) ![](https://img.shields.io/github/stars/microsoft/unilm.svg?style=social)|⭐️ |
 
 ### 📖IO/FLOPs-Aware/Sparse Attention ([©️back👆🏻](#paperlist))
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