Add task categories, paper link, and dataset details

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by nielsr HF Staff - opened
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  1. README.md +44 -10
README.md CHANGED
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  ---
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  license: apache-2.0
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- pretty_name: Blade
 
 
 
 
 
 
 
 
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  ---
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- If you use this dataset or paper cite this paper.
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- Bibtext :
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  @misc{shuvo2026politesurfacewrongpractice,
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  title={Polite on the Surface, Wrong in Practice: A Curated Dataset for Fixing Honorific Failures in Multilingual Bangla Generation},
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  author={Md. Asaduzzaman Shuvo and Mahedi Hasan and Md. Tashin Parvez and Azizul Haque Noman and Md. Shafayet Hossain Ovi},
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  primaryClass={cs.CL},
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  url={https://arxiv.org/abs/2605.22487},
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  }
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-
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-
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- ------------------------------------------------
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-
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- from datasets import load_dataset
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-
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- ds = load_dataset("mdshuvo25/BLADE")
 
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  ---
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  license: apache-2.0
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+ pretty_name: BLADE
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+ task_categories:
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+ - text-generation
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+ language:
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+ - bn
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+ tags:
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+ - bangla
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+ - bengali
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+ - instruction-tuning
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  ---
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+ # BLADE: Bangla Application and Dialogue Generation Dataset
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+ This repository contains the BLADE (BangLa Application and DialoguE generation) dataset introduced in the paper [Polite on the Surface, Broken in Practice: A Curated Dataset for Fixing Generation and Register Failures in Low-Resource Bangla Text Generation](https://huggingface.co/papers/2605.22487).
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+ GitHub Repository: [Bangla_Application_LLM](https://github.com/ashuvo25/Bangla_Application_LLM)
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+
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+ ## Dataset Summary
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+
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+ **BLADE** (BangLa Application and DialoguE generation) is a culturally aligned instruction-tuning dataset comprising **4,196 meticulously curated interaction pairs** in Bengali. It is designed to help train and evaluate language models for generating formal correspondence (such as applications and letters) and dialogues in Bengali, addressing the pragmatic gap and honorific inconsistencies in low-resource Bangla text generation.
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+
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+ ### Dataset at a Glance
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+ - **Total Samples**: 4,196 prompt-response pairs
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+ - **Unique Topics**: 2,008 distinct subjects covering a wide variety of formal letters
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+ - **Language**: Bengali/Bangla
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+ - **Average Prompt Length**: 8 tokens
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+ - **Average Response Length**: 1,340 tokens
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+ - **Maximum Sequence Length**: 1,942 tokens
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+
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+ The dataset covers a diverse range of topics and recipients, including school headmasters, company managers, and government officials, making it a valuable resource for developing language models capable of understanding the nuances of formal Bengali writing.
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+
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+ ## Sample Usage
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+ You can load this dataset using the Hugging Face `datasets` library:
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+ ```python
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+ from datasets import load_dataset
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+
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+ ds = load_dataset("mdshuvo25/BLADE")
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+ ```
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+
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+ ## Citation
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+
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+ If you use this dataset or paper, please cite:
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+
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+ ```bibtex
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  @misc{shuvo2026politesurfacewrongpractice,
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  title={Polite on the Surface, Wrong in Practice: A Curated Dataset for Fixing Honorific Failures in Multilingual Bangla Generation},
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  author={Md. Asaduzzaman Shuvo and Mahedi Hasan and Md. Tashin Parvez and Azizul Haque Noman and Md. Shafayet Hossain Ovi},
 
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  primaryClass={cs.CL},
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  url={https://arxiv.org/abs/2605.22487},
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  }
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+ ```