--- license: cc-by-4.0 task_categories: - text-generation - summarization - image-to-text language: - bn tags: - bengali - news - headline-generation - multimodal - vision-language - nlp size_categories: - 1M Paper Coming Soon

[![Paper](https://img.shields.io/badge/arXiv-coming--soon-red)](https://arxiv.org/abs/0000.00000) [![GitHub](https://img.shields.io/badge/GitHub-Code-blue)](https://github.com/dipta007/bengali-news-headline) [![Text-Only Version](https://img.shields.io/badge/HuggingFace-Barta_(text--only)-yellow)](https://huggingface.co/datasets/dipta007/Barta) ## Overview **BartaLens** (বার্তা + Lens) is a large-scale multimodal Bengali news corpus pairing articles with their associated news images. It is designed for training and evaluating vision-language models on Bengali headline generation. Key features: - **1.2M+ articles** with associated news images - **Three splits** (train / validation / test) for reproducible evaluation - **Multimodal** — each article paired with its news photograph - **Diverse sources** from major Bangladeshi news outlets ## Dataset Statistics | Split | Rows | |-------|-----:| | train | 1,219,442 | | validation | 5,000 | | test | 15,000 | ## Loading the Dataset ```python from datasets import load_dataset # Load train split dataset = load_dataset("dipta007/BartaLens", split="train") # Load test split test = load_dataset("dipta007/BartaLens", split="test") # Access an example example = dataset[0] image = example["image"] # PIL Image headline = example["headline"] article = example["article"] ``` ## Data Fields | Field | Type | Description | |-------|------|-------------| | `id` | string | Unique identifier | | `article` | string | Full article body in Bengali | | `headline` | string | Article headline in Bengali | | `source` | string | News outlet name | | `category` | string | News category in Bengali | | `image` | Image | Associated news photograph (PIL Image) | ## Intended Use - **Multimodal headline generation** — generate headlines from article text + image - **Vision-language model** fine-tuning (e.g., Gemma, Qwen VLMs with LoRA) - **Image-guided summarization** — leverage visual context for better summaries - **Bengali VLM benchmarking** — evaluate multimodal understanding in Bengali - **Cross-modal retrieval** — match news images to articles ## Related Datasets - [**Barta**](https://huggingface.co/datasets/dipta007/Barta) — text-only version (1.7M articles, full corpus without image filtering) ## Citation ```bibtex @article{BartaLens2025, title={BartaLens: A Multimodal Bengali News Corpus for Headline Generation}, author={Shubhashis Roy Dipta}, year={2025} } ```