416 datasets found

Groups: Question Answering Organizations: No Organization

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  • Wiki-BM

    The Wiki-BM dataset is a benchmark for the Split and Rephrase task, consisting of Wikipedia data.

  • BiSECT

    The BiSECT dataset is a benchmark for the Split and Rephrase task, consisting of bitexts.

  • WebSplit

    The WebSplit dataset is a benchmark for the Split and Rephrase task, consisting of RDF semantic tuples.

  • LAMBADA

    The dataset used in the paper is a corpus of text containing approximately 10,000 examples, each a sequence of sentences extracted from books.

  • WirelessLLM

    The WirelessLLM dataset contains questions and answers about wireless communication systems, focusing on questions with a single entity and relation.

  • SPEC5G

    The SPEC5G dataset contains questions and answers about 5G cellular network protocols, focusing on questions with a single entity and relation.

  • StandardsQA

    The StandardsQA dataset contains questions and answers about telecommunications standards, focusing on questions with a single entity and relation.

  • TeleQnA

    The TeleQnA dataset contains questions and answers about telecommunications knowledge, focusing on questions with a single entity and relation.

  • EuSQuAD

    EuSQuAD: Automatically Translated and Aligned SQuAD2.0 for Basque

  • TruthfulQA

    The TruthfulQA dataset is a dataset that contains 817 questions designed to evaluate language models' preference to mimic some human falsehoods.

  • BioASQ

    The BioASQ dataset contains questions and answers from various sources, including Wikipedia and biomedical literature.

  • BioASQ 2016 Task 4b

    The dataset used in this paper is the BioASQ 2016 Task 4b dataset, which contains questions along with their relevant documents.

  • SciFact

    The SciFact dataset is a collection of scientific fact questions and their corresponding answers.

  • DEFT

    DEFT consists of two categories of definitions: a) Contracts: involving 2,433 sentences from the 2017 SEC contract filing, and b) Textbook: involving 21,303 sentences from...

  • Yin-Yang dataset

    The Yin-Yang dataset is a benchmark for evaluating the performance of question answering systems.

  • FVQA

    FVQA is a fact-based visual question answering dataset, containing 2190 images and 5826 (question, answer) pairs, with supporting facts selected from knowledge bases.

  • Visual7W

    The Visual7W dataset for Visual Question Answering (VQA). The dataset contains 7,000 images with 7,000 queries.

  • Visual Question Answering as Reading Comprehension

    Visual question answering (VQA) demands simultaneous comprehension of both the image visual content and natural language questions. In some cases, the reasoning needs the help...

  • Natural Questions and TriviaQA

    The dataset used in the paper is Natural Questions and TriviaQA, two popular datasets for open-domain question answering.

  • Question Answering Based Clinical Text Structuring

    Clinical text structuring is a critical and fundamental task for clinical research. Traditional methods such as task-specific end-to-end models and pipeline models usually...