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+{"paper_url": "https://huggingface.co/papers/2405.09335", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [GeMQuAD : Generating Multilingual Question Answering Datasets from Large Language Models using Few Shot Learning](https://huggingface.co/papers/2404.09163) (2024)\n* [Enhancing Pre-Trained Generative Language Models with Question Attended Span Extraction on Machine Reading Comprehension](https://huggingface.co/papers/2404.17991) (2024)\n* [Asking and Answering Questions to Extract Event-Argument Structures](https://huggingface.co/papers/2404.16413) (2024)\n* [Better Synthetic Data by Retrieving and Transforming Existing Datasets](https://huggingface.co/papers/2404.14361) (2024)\n* [Synthesizing Conversations from Unlabeled Documents using Automatic Response Segmentation](https://huggingface.co/papers/2406.03703) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}