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README.md

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 ## Interaction
-Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for (multimodal) LLMs!
-
-Data-Juicer 是一个一站式数据处理系统，为大模型提供更高质量、更丰富、更易”消化“的数据！
+Data-Juicer is a one-stop system to process text and multimodal data for and with foundation models (typically LLMs). We provide a [playground](http://8.138.149.181/) with a managed JupyterLab.
+See more details in our homepage: https://github.com/modelscope/data-juicer
 
 ## News 
-- [2024-07-17] We utilized the Data-Juicer [Sandbox Laboratory Suite](https://github.com/modelscope/data-juicer/blob/main/docs/Sandbox.md) to systematically optimize data and models through an co-development workflow between data and models, achieving a new top spot on the [VBench](https://huggingface.co/spaces/Vchitect/VBench_Leaderboard) text-to-video leaderboard. The related achievements have been compiled and published in a [paper](http://arxiv.org/abs/2407.11784), and the model has been released on the [ModelScope](https://modelscope.cn/models/Data-Juicer/Data-Juicer-T2V) and [HuggingFace](https://huggingface.co/datajuicer/Data-Juicer-T2V) platforms.
-- [2024-07-12] Our *awesome list of MLLM-Data* has evolved into a systemic [survey](https://arxiv.org/abs/2407.08583) from model-data co-development perspective. Welcome to [explore](docs/awesome_llm_data.md) and contribute!
-- [2024-06-01] ModelScope-Sora "Data Directors" creative sprint—Our third data-centric LLM competition has kicked off! Please visit the competition's [official website](https://tianchi.aliyun.com/competition/entrance/532219) for more information.
-- [2024-03-07] We release **Data-Juicer [v0.2.0](https://github.com/alibaba/data-juicer/releases/tag/v0.2.0)** now! 
-In this new version, we support more features for **multimodal data (including video now)**, and introduce **[DJ-SORA](docs/DJ_SORA.md)** to provide open large-scale, high-quality datasets for SORA-like models.
-- [2024-02-20] We have actively maintained an *awesome list of LLM-Data*, welcome to [visit](docs/awesome_llm_data.md) and contribute!
-- [2024-02-05] Our paper has been accepted by SIGMOD'24 industrial track!
-- [2024-01-10] Discover new horizons in "Data Mixture"—Our second data-centric LLM competition has kicked off! Please visit the competition's [official website](https://tianchi.aliyun.com/competition/entrance/532174) for more information.
-- [2024-01-05] We release **Data-Juicer v0.1.3** now! 
-In this new version, we support **more Python versions** (3.8-3.10), and support **multimodal** dataset [converting](tools/multimodal/README.md)/[processing](docs/Operators.md) (Including texts, images, and audios. More modalities will be supported in the future).
-Besides, our paper is also updated to [v3](https://arxiv.org/abs/2309.02033).
+- [2025-01-11] We release our 2.0 paper, [Data-Juicer 2.0: Cloud-Scale Adaptive Data Processing for Foundation Models](https://dail-wlcb.oss-cn-wulanchabu.aliyuncs.com/data_juicer/DJ2.0_arXiv_preview.pdf). It now can process 70B data samples within 2.1h, using 6400 CPU cores on 50 Ray nodes from Alibaba Cloud cluster, and deduplicate 5TB data within 2.8h using 1280 CPU cores on 8 Ray nodes.
+- [2025-01-03] We support post-tuning scenarios better, via 20+ related new [OPs](https://github.com/modelscope/data-juicer/releases/tag/v1.0.2), and via unified [dataset format](https://github.com/modelscope/data-juicer/releases/tag/v1.0.3) compatiable to LLaMA-Factory and ModelScope-Swift.
+- [2025-12-17] We propose *HumanVBench*, which comprises 17 human-centric tasks with synthetic data, benchmarking video-MLLMs' capabilities from views of inner emotion and outer manifestations. See more details in our [paper](https://arxiv.org/abs/2412.17574), and try to [evaluate](https://github.com/modelscope/data-juicer/tree/HumanVBench) your models with it.
+- [2024-11-22] We release DJ [v1.0.0](https://github.com/modelscope/data-juicer/releases/tag/v1.0.0), in which we refactored Data-Juicer's *Operator*, *Dataset*, *Sandbox* and many other modules for better usability, such as supporting fault-tolerant, FastAPI and adaptive resource management.
+- [2024-08-25] We give a [tutorial](https://modelscope.github.io/data-juicer/_static/tutorial_kdd24.html) about data processing for multimodal LLMs in KDD'2024.