emrekuruu/TATDQA

TAT-DQA

TAT-DQA is one of the 11 retrieval benchmarks used in RetrievalRouter: Joint Modality and Architecture Selection for Document Retrieval (EMNLP 2026). Each record pairs a rendered page image, a query, and the page's extracted text, supporting both text-based and multimodal retrieval evaluation.

• 📄 Paper: https://arxiv.org/pdf/2608.25625
• 💻 Code: https://github.com/emrekuruu/retrieval-router
• 🤗 Collection: https://huggingface.co/collections/emrekuruu/retrieval-router

Source benchmark: T2-RAGBench (Strich et al., 2025). This repository repackages that benchmark for the RetrievalRouter experiments; if you use it, please cite the original source as well.

Citation

@misc{kuru2026retrievalrouterjointmodalityarchitecture,
      title={RetrievalRouter: Joint Modality and Architecture Selection for Document Retrieval}, 
      author={Emre Kuru and Mehmet Onur Keskin and Reza Farahbakhsh and Noel Crespi},
      year={2026},
      eprint={2608.25625},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2608.25625}, 
}

@misc{strich2025t2ragbench,
  title={T$^2$-RAGBench: Text-and-Table Benchmark for Evaluating Retrieval-Augmented Generation},
  author={Strich, Jan and Isgorur, Enes Kutay and Trescher, Maximilian and Biemann, Chris and Semmann, Martin},
  year={2025},
  eprint={2506.12071},
  archivePrefix={arXiv},
  primaryClass={cs.IR}
}