420 datasets found

XNMT is a neural machine translation toolkit that focuses on modular code design, making it easy to swap in and out different parts of the model.

The dataset used in the paper is the Stanford Sentiment Treebank (SST) dataset, which contains standard train/dev/test sets and two subtasks: binary sentence classification or...

The dataset consists of approximately 10 million question-answer pairs from multiple languages covering diverse fields such as math and language, and strong variation in...

A fast and accurate one-stage approach to visual grounding

Cooperative holistic understanding for visual grounding on point clouds through instance multi-level contextual referring

Free-form description guided 3D visual graph network for 3D object grounding in point clouds

A dataset of 22,000 cellular documents, including technical specifications, change requests, and technical reports.

The dataset used in the paper to evaluate attribution scores.

The dataset used in this paper is the Anthropic Helpfulness and Harmlessness (HH) dataset, which features a wide variety of user queries and is commonly used for training...

The Multilingual Eye-movement Corpus (MECO) is a collection of eye-tracking data that has been collected from participants reading texts in 13 languages.

The dataset used in the paper is a collection of natural human instructions for a 3D room containing everyday objects. The instructions are used to train an agent to follow...

NLSC uses two pre-trained models, one uses 19.7B words from 700 dimensions trained on English tweets, and the other uses 1.7B words from 700 dimensions trained on Wikipedia...

The Phi-2 dataset is a collection of language models used to evaluate the performance of language models.

STAMP 4 NLP is an instantiable, iterative, and incremental process model for developing natural language processing applications with a focus on quality, business value, and...

A comprehensive dataset for post-OCR parsing and receipt understanding, specifically designed to enhance OCR and information extraction from receipts in multilingual contexts...

In-context learning (ICL) is an important capability of Large Language Models (LLMs), enabling these models to dynamically adapt based on specific, in-context exemplars, thereby...

The dataset used in the paper is CIFAR-10, FEMNIST, and IMDB. The authors used these datasets to evaluate the performance of the EmbracingFL framework.

The Virtual Language Observatory (VLO) is a web application equipped with easy-to-use Natural Language Processing tools.

Propose a method for evaluating gender bias in contextualised word embeddings.

Propose a method for evaluating gender bias in contextualised word embeddings.