Update README.md

README.md

@@ -143,11 +143,11 @@ Amir Gholami\* , Sehoon Kim\* , Zhen Dong\* , Zhewei Yao\* , Michael W. Mahoney,
 - [[arxiv](https://arxiv.org/abs/2306.07629)] SqueezeLLM: Dense-and-Sparse Quantization [[code](https://github.com/SqueezeAILab/SqueezeLLM)]
 - [[arxiv](https://arxiv.org/abs/2306.12929)] Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing
 - [[arxiv](https://arxiv.org/abs/2306.13515)] Binary domain generalization for sparsifying binary neural networks [__`bnn`__]
-- [[arXiv](https://arxiv.org/abs/2307.09782)] ZeroQuant-FP: A Leap Forward in LLMs Post-Training W4A8 Quantization Using Floating-Point Formats
-- [[arXiv](https://arxiv.org/abs/2305.12356)] Integer or Floating Point? New Outlooks for Low-Bit Quantization on Large Language Models
-- [[arXiv](https://arxiv.org/abs/2304.01089)] RPTQ: Reorder-based Post-training Quantization for Large Language Models [[code](https://github.com/hahnyuan/RPTQ4LLM)]
-- [[arXiv](https://arxiv.org/abs/2306.02272)] OWQ: Lessons learned from activation outliers for weight quantization in large language models
-- [[arXiv](https://arxiv.org/abs/2305.14152)] Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
+- [[arxiv](https://arxiv.org/abs/2307.09782)] ZeroQuant-FP: A Leap Forward in LLMs Post-Training W4A8 Quantization Using Floating-Point Formats
+- [[arxiv](https://arxiv.org/abs/2305.12356)] Integer or Floating Point? New Outlooks for Low-Bit Quantization on Large Language Models
+- [[arxiv](https://arxiv.org/abs/2304.01089)] RPTQ: Reorder-based Post-training Quantization for Large Language Models [[code](https://github.com/hahnyuan/RPTQ4LLM)]
+- [[arxiv](https://arxiv.org/abs/2306.02272)] OWQ: Lessons learned from activation outliers for weight quantization in large language models
+- [[arxiv](https://arxiv.org/abs/2305.14152)] Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
 
 ### 2022