416 datasets found

The authors used several question-answering datasets, including CoQA, TriviaQA, and Natural Questions.

The dataset used for the experiments across ten models– ranging from bag-of-words models to pre-trained transformers– and find that a model having higher AUC does not necessarily...

FUNSD dataset contains questions answerable using Wikidata as the knowledge graph, focusing on questions with a single entity and relation.

CORD dataset contains questions answerable using Wikidata as the knowledge graph, focusing on questions with a single entity and relation.

The dataset is used for neural collaborative filtering, which is a type of collaborative filtering that uses neural networks to learn the relationships between users and items.

The dataset is used for training and evaluating the MS MARCO model, a question answering model.

Visual Question Answering (VQA) has achieved great success thanks to the fast development of deep neural networks (DNN). On the other hand, the data augmentation, as one of the...

The IMDB-RLHF-Pair dataset is generated by IMDB, and responses with positive sentiment are preferred.

The Stack-Exchange-Paired dataset contains questions and answers from the Stack Overflow dataset, where answers with more votes are preferred.

The dataset used for FAQ sentence labeling.

The XQuAD dataset is a multilingual question answering dataset.

Parameter-efficient fine-tuning (PEFT) using labeled task data can significantly improve the performance of large language models (LLMs) on the downstream task. However, there...

Wizard of Wikipedia is a recent, large-scale dataset of multi-turn knowledge-grounded dialogues between a “apprentice” and a “wizard”, who has access to information from...

The dataset used in the paper is a synthetic dataset for off-policy contextual bandits, with contexts x ∈ X, a finite set of actions A, and bounded real rewards r ∈ A → [0, 1].

Visual dialog is a multi-round extension for VQA. The interactions between the image and multi-round question-answer pairs (history) are progressively changing, and the...

Visual dialog is a challenging task that requires the comprehension of the semantic dependencies among implicit visual and textual contexts. This task can refer to the relation...

Legal case retrieval is a critical process for modern legal information systems. This paper proposes CaseEncoder, a pre-trained encoder that utilizes fine-grained legal...

The paper discusses the use of multi-objective Bayesian optimization for hyperparameter transfer in topic models.

Generalized Category Discovery (GCD) aims to recognize both known and novel categories from a set of unlabeled data, based on another dataset labeled with only known categories.

MathQA is an English mathematical problems dataset at GRE level. The original MathQA dataset is annotated in a different way from Math23k with many pre-defined operations.