Update README.md

README.md

@@ -25,7 +25,7 @@ task_categories:
 
 <!-- This dataset is part of **FORGE**, a comprehensive benchmark for **FO**rming **R**aw user behavior sequences and **G**enerative r**E**trieval in Industrial Datasets, as presented in the paper [FORGE: Forming Semantic Identifiers for Generative Retrieval in Industrial Datasets](https://huggingface.co/papers/2509.20904). The FORGE benchmark aims to address challenges in semantic identifiers (SIDs) for generative retrieval (GR) by providing a large-scale public dataset with multimodal features. -->
 
-Specifically, this `AL-GR/Origin-Sequence-Data` repository contains the foundational **raw user behavior sequences** for the `AL-GR` ecosystem. It represents the data *before* it is formatted into the instruction-following prompts used for training Large Language Models (LLMs) in generative retrieval tasks. The full FORGE dataset comprises 14 billion user interactions and multimodal features of 250 million items sampled from Taobao, one of the biggest e-commerce platforms in China.
+<!-- Specifically, this `AL-GR/Origin-Sequence-Data` repository contains the foundational **raw user behavior sequences** for the `AL-GR` ecosystem. It represents the data *before* it is formatted into the instruction-following prompts used for training Large Language Models (LLMs) in generative retrieval tasks. The full FORGE dataset comprises 14 billion user interactions and multimodal features of 250 million items sampled from Taobao, one of the biggest e-commerce platforms in China. -->
 
 Each row in this dataset (`Origin-Sequence-Data`) represents a step in a user's journey, consisting of a sequence of previously interacted items (`user_history`) and the next item they interacted with (`target_item`). All item IDs have been anonymized into short, unique strings.