536 datasets found

The SHG-VQA model predicts a situation hyper-graph structure composed of existing actions and relations in the input video.

The paper proposes a novel method, REPROMPT, for optimizing the step-by-step instructions in the prompt of LLM agents based on the chat history obtained from interactions with...

SemEval-2016 (Task 3A) is a sentence-level QA dataset, containing 1.8k/0.2k/0.3k train/dev/test examples. Each example consists of a community question by a user and 10 comments.

Question answering (QA) is a long-standing challenge in NLP, and the community has introduced several paradigms and datasets for the task over the past few years. These...

A video story question answering dataset containing 24,282 questions about 207 episodes of The Big Bang Theory.

MARGE is a pre-trained sequence-to-sequence model learned with an unsupervised multi-lingual multi-document paraphrasing objective.

The Alquist dialogue system is designed to conduct a coherent and engaging conversation on popular topics.

LogicVista is a comprehensive evaluation benchmark for multimodal large language models (MLLMs) in visual contexts. It assesses the integrated logical reasoning capabilities of...

The authors created a dataset called ShortcutQA, which is a curated dataset generated by their framework for future research.

The dataset used in the paper is a collection of dialogues and prompts for training a model to perform retrieval-augmented generation (RAG) based summarization. The dataset is...

SocialIQA is a 3-way multiple-choice QA dataset to evaluate the understanding of social commonsense knowledge.

CommonsenseQA and OpenBookQA are two of the most widely used commonsense reasoning benchmarks.

Ontology-based question answering over corporate structured data

The ConceptNet 5.5 dataset is an open multilingual graph of general knowledge.

A neural-symbolic reasoner for Commonsense Knowledge Graphs (CKGs) that leverages a relation prediction module and weak unification.

A few existing datasets for asking clarification questions

A dataset for pragmatic evaluation of clarifying questions and fact-level masking

Generative Agents framework by Park et al., aimed at enhancing the efficient retrieval of key events for general-purpose LLM agents.

Explanation Gold Standards (XGSs) are emerging as a fundamental enabling tool for step-wise and explainable Natural Language Inference (NLI).

The CSQA dataset is a widely used benchmark dataset for conversational KBQA, consisting of around 200K dialogues where training set, validation set and testing set contain 153K,...