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README.md

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 - ![new](https://img.alicdn.com/imgextra/i4/O1CN01kUiDtl1HVxN6G56vN_!!6000000000764-2-tps-43-19.png) [02-17-2024] EasyTPP supports HuggingFace dataset API: all datasets have been published in [HuggingFace Repo](https://huggingface.co/easytpp) and see [tutorial notebook](https://github.com/ant-research/EasyTemporalPointProcess/blob/main/notebooks/easytpp_1_dataset.ipynb) for an example of usage.
+- ![new](https://img.alicdn.com/imgextra/i4/O1CN01kUiDtl1HVxN6G56vN_!!6000000000764-2-tps-43-19.png) [01-16-2024] Our paper [EasyTPP: Towards Open Benchmarking Temporal Point Process] is accepted by ICLR'2024! 
 - ![new](https://img.alicdn.com/imgextra/i4/O1CN01kUiDtl1HVxN6G56vN_!!6000000000764-2-tps-43-19.png) [09-30-2023] We published two textual event sequence datasets [GDELT](https://drive.google.com/drive/folders/1Ms-ATMMFf6v4eesfJndyuPLGtX58fCnk) and [Amazon-text-review](https://drive.google.com/drive/folders/1-SLYyrl7ucEG7NpSIF0eSoG9zcbZagZw) that are used in our paper [LAMP](https://arxiv.org/abs/2305.16646), where LLM can be applied for event prediction! See [Documentation](https://ant-research.github.io/EasyTemporalPointProcess/user_guide/dataset.html#preprocessed-datasets) for more details.
 - ![new](https://img.alicdn.com/imgextra/i4/O1CN01kUiDtl1HVxN6G56vN_!!6000000000764-2-tps-43-19.png) [09-30-2023] Two of our papers [Language Model Can Improve Event Prediction by Few-Shot Abductive Reasoning](https://arxiv.org/abs/2305.16646) (LAMP) and [Prompt-augmented Temporal Point Process for Streaming Event Sequence](https://arxiv.org/abs/2310.04993) (PromptTPP) are accepted by NeurIPS'2023!
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