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Quora Dataset
The dataset used in this paper is a real-world dataset from Quora, containing 372,818 questions and 1,739,222 answers associated with topics, upvotes, timestamps, etc. -
Stanford Question Answering Dataset (SQuAD 2.0)
The Stanford Question Answering Dataset (SQuAD 2.0) supplements the SQuAD 1.1 with over 50K unanswerable questions. -
Stanford Question Answering Dataset (SQuAD 1.1)
The Stanford Question Answering Dataset (SQuAD 1.1) is a dataset of more than 100K questions which all can be answered by locating a span of text from the corresponding context... -
Music-AVQA
The Music-AVQA dataset contains multiple question-and-answer pairs, with 9,288 videos and 45,867 question-and-answer pairs. -
Audio-Visual Question Answering
Audio-visual question answering (AVQA) requires reference to video content and auditory information, followed by correlating the question to predict the most precise answer. -
MQUAKE-CF and MQUAKE-T datasets
The MQUAKE-CF and MQUAKE-T datasets comprise multi-hop questions that are based on real-world facts, where the edited facts are counterfactual. -
Retrieval-Augmented Knowledge Editing for Multi-Hop Question Answering in Lan...
Large Language Models (LLMs) have shown proficiency in question-answering tasks but often struggle to integrate real-time knowledge updates, leading to potentially outdated or... -
Conceptual Captions
The dataset used in the paper "Scaling Laws of Synthetic Images for Model Training". The dataset is used for supervised image classification and zero-shot classification tasks. -
Yahoo Answers
The dataset Yahoo Answers contains 730,000 questions and answers. -
Measuring Machine Intelligence through Visual Question Answering
Measuring machine intelligence through visual question answering. -
Exploring Models and Data for Image Question Answering
Exploring models and data for image question answering. -
VQA: Visual Question Answering
Visual Question Answering (VQA) has emerged as a prominent multi-discipline research problem in both academia and industry. -
Hierarchical Question-Image Co-Attention for Visual Question Answering
A number of recent works have proposed attention models for Visual Question Answering (VQA) that generate spatial maps highlighting image regions relevant to answering the... -
Bing dataset
The Bing dataset is a large-scale dataset for natural language understanding and question answering. -
MS MARCO dataset
The MS MARCO dataset is a large-scale dataset for natural language understanding and question answering. -
Task-Oriented Language Grounding
The dataset used in the paper is a set of 55 training instructions and 15 test instructions for zero-shot evaluation. -
VideoStreaming
A novel approach to tackle the complexities of long video understanding with large language models (LLMs). Our proposed memory-propagated streaming encoding architecture...
