420 datasets found

The dataset is used for training and testing response selection models for multi-turn conversations.

A dataset for multi-turn dialogue reasoning

A lightweight fully convolutional network for multi-view response selection

The BigBench dataset is a collection of 12 challenging language model reasoning tasks.

The TEL-NLP dataset is a collection of Telugu text data for four NLP tasks: sentiment analysis, emotion identification, hate speech detection, and sarcasm detection.

Visual grounding is the task of localizing a language query in an image. The output is often a bounding box as drawn in the yellow color.

The Flickr30K Entities dataset consists of 31,783 images each matched with 5 captions. The dataset links distinct sentence entities to image bounding boxes, resulting in 70K...

The Vision-and-Language Navigation (VLN) task gives a global natural sentence I = {w0,..., wl} as an instruction, where wi is a word token while the l is the length of the...

The ToxicSpans dataset is a subset of the Civil Comments dataset, containing toxic spans.

The dataset used for probing LLMs for hate speech detection, including HateXplain, implicit hate, and ToxicSpans datasets.

Visual instruction tuning.

Flamingo: a visual language model for few-shot learning.

Audio-visual scene-aware dialog.

ChatBridge is a multimodal language model capable of perceiving real-world multimodal information, as well as following instructions, thinking, and interacting with humans in...

Large language models (LLMs) have achieved significant performance progress in various natural language processing applications. However, LLMs still struggle to meet the strict...

TruthX: Alleviating Hallucinations by Editing Large Language Models

This work presents StrAE: a Structured Autoencoder framework that through strict adherence to explicit structure, and use of a novel contrastive objective over tree-structured...

The ALFRED benchmark includes 25,743 trajectory-instruction pairs, covering 7 different task types with varying levels of complexity.

The ShapeNeRF–Text dataset consists of 40K paired NeRFs and language annotations for ShapeNet objects.

The dataset used in this paper is not explicitly described. However, it is mentioned that the authors used the Wikitext-2 dataset for text generation tasks.