Papers with data collection paradigm

2 papers
SIMMC-VR: A Task-oriented Multimodal Dialog Dataset with Situated and Immersive VR Streams (2023.acl-long)

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Challenge: Existing models lack a large-scale benchmark to capture user–assistant interactions . et al., 2022: 145-160.
Approach: They propose a video-grounded task-oriented dialog dataset that captures real-world AI-assisted user scenarios in VR.
Outcome: The proposed dataset captures real-world AI-assisted user scenarios in VR.
HellaSwag: Can a Machine Really Finish Your Sentence? (P19-1)

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Challenge: Existing commonsense models struggle to perform inferences that are trivial for humans, but are often misclassified by state-of-the-art models.
Approach: They propose a dataset that is adversarial to state-of-the-art commonsense reasoning and use it to build a model that is surprisingly robust.
Outcome: The proposed dataset is compared with existing models and scaled up towards a critical 'Goldilocks zone' wherein generated text is ridiculous to humans, yet often misclassified by state-of-the-art models.

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