11 datasets found

The Stanford Multi-turn, Multi-domain Dialogue Dataset is a dataset for language understanding in task-oriented dialogue systems. It contains a large number of training...

The Airline Travel Information System dataset (ATIS) is a dataset for language understanding in task-oriented dialogue systems. It contains 4978 training utterances from Class A...

Ref-DAVIS17 is an extension of the DAVIS17 dataset, where it enhances the dataset by providing language descriptions for each specific object present in the videos.

Referring video object segmentation (RVOS) aims to accurately segment the target object in the video with the guidance of given language expressions.

The dataset is used for instruction-tuning of LLMs in multiple languages using reinforcement learning from human feedback.

The dataset used for pre-training language models, containing a large collection of text documents.

G-Ref is a dataset for referring image segmentation, comprising 104K referring language expressions for around 55K objects in about 27K images.

A Large Video Description Dataset for Bridging Video and Language.

Ref-Youtube-VOS is an extensive referring video object segmentation dataset that comprises approximately 15,000 referring expressions associated with more than 3,900 videos.

The dataset used in the paper is a benchmark for referring expression grounding, containing 142,210 referring expressions for 50,000 referents in 19,994 images.

This paper proposes BERT, a pre-trained deep bidirectional transformer for language understanding.