Results 1 to 10 of about 1,338,465 (400)

A Span-Extraction Dataset for Chinese Machine Reading Comprehension [PDF]

open access: yesEMNLP 2019 5886-5891, 2018
Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention. However, the existing reading comprehension datasets are mostly in English. In this paper, we introduce a Span-Extraction dataset for Chinese machine reading comprehension to add language diversities in this area.
Che, Wanxiang   +7 more
arxiv   +5 more sources

STARC: Structured Annotations for Reading Comprehension [PDF]

open access: yesarXiv, 2020
We present STARC (Structured Annotations for Reading Comprehension), a new annotation framework for assessing reading comprehension with multiple choice questions. Our framework introduces a principled structure for the answer choices and ties them to textual span annotations.
Berzak, Yevgeni   +2 more
arxiv   +3 more sources

DREAM: A Challenge Dataset and Models for Dialogue-Based Reading Comprehension [PDF]

open access: yesarXiv, 2019
We present DREAM, the first dialogue-based multiple-choice reading comprehension dataset. Collected from English-as-a-foreign-language examinations designed by human experts to evaluate the comprehension level of Chinese learners of English, our dataset contains 10,197 multiple-choice questions for 6,444 dialogues.
Kai Sun   +5 more
arxiv   +3 more sources

SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension [PDF]

open access: yesarXiv.org, 2023
Based on powerful Large Language Models (LLMs), recent generative Multimodal Large Language Models (MLLMs) have gained prominence as a pivotal research area, exhibiting remarkable capability for both comprehension and generation. In this work, we address
Bohao Li   +5 more
semanticscholar   +1 more source

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2019
We present BART, a denoising autoencoder for pretraining sequence-to-sequence models. BART is trained by (1) corrupting text with an arbitrary noising function, and (2) learning a model to reconstruct the original text.
M. Lewis   +7 more
semanticscholar   +1 more source

Comprehensive comprehensions [PDF]

open access: yesProceedings of the ACM SIGPLAN workshop on Haskell workshop, 2007
We propose an extension to list comprehensions that makes it easy to express the kind of queries one would write in SQL using ORDER BY, GROUP BY, and LIMIT. Our extension adds expressive power to comprehensions, and generalises the SQL constructs that inspired it. It is easy to implement, using simple desugaring rules.
Simon Jones, Philip Wadler
openaire   +2 more sources

High tibial osteotomy: A review of the readability and quality of patientinformation on the internet [PDF]

open access: yesHealth Promotion Perspectives, 2021
Background: High tibial osteotomy (HTO) is a common procedure performed for unicompartmental knee osteoarthritis (OA). Patients are increasingly using the internet to research surgical procedures to help aid decision making.
Matthew Clark   +4 more
doaj   +1 more source

SQuAD: 100,000+ Questions for Machine Comprehension of Text [PDF]

open access: yesConference on Empirical Methods in Natural Language Processing, 2016
We present the Stanford Question Answering Dataset (SQuAD), a new reading comprehension dataset consisting of 100,000+ questions posed by crowdworkers on a set of Wikipedia articles, where the answer to each question is a segment of text from the ...
Pranav Rajpurkar   +3 more
semanticscholar   +1 more source

TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2017
We present TriviaQA, a challenging reading comprehension dataset containing over 650K question-answer-evidence triples. TriviaQA includes 95K question-answer pairs authored by trivia enthusiasts and independently gathered evidence documents, six per ...
Mandar Joshi   +3 more
semanticscholar   +1 more source

Anchoring Code Understandability Evaluations Through Task Descriptions [PDF]

open access: yesIn Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension (ICPC 2022). Association for Computing Machinery, New York, NY, USA, 133-140, 2022
In code comprehension experiments, participants are usually told at the beginning what kind of code comprehension task to expect. Describing experiment scenarios and experimental tasks will influence participants in ways that are sometimes hard to predict and control.
arxiv   +1 more source

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