43 datasets found

The WikiText-2 dataset is a benchmark for evaluating the performance of large language models.

The dataset used in the paper is not explicitly mentioned, but it is mentioned that the authors trained a GPT2 transformer language model on the C4 dataset.

Large Language Models (LLMs) have greatly advanced the natural language processing paradigm. However, the high computational load and huge model sizes pose a grand challenge for...

The dataset used in this study to analyze the self-assessment behavior of Large language models.

This dataset is used to study the moral profiles of large language models.

This dataset is used to assess the moral reasoning capabilities of large language models.

The LLaMA dataset is a large language model dataset used in the paper.

The dataset used in this paper is a large-scale dataset for evaluating LLMs, which is used to train and evaluate the Chatbot Arena model.

The dataset used in this paper is a large-scale dataset for evaluating LLMs, which is used to train and evaluate the Arena-Hard model.

The dataset used in this paper is a large-scale real-world LLM conversation dataset, which is used to train and evaluate the LMSYS ChatBot Arena model.

The dataset used in this paper is a large-scale conversational data, which is used to train and evaluate the WizardLM-β model.

The dataset used in the paper is OPT-66B, a large language model, and Llama2-70B, another large language model.

OpenAssistant Conversations– Democratizing Large Language Model Alignment

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the ELI5, FinanceQA, MultiNews, and QMSum datasets.

The Inducing Anxiety in Large Language Models Increases Exploration and Bias dataset contains anxiety-inducing scenarios for large language models.

This paper presents a review of recent advances in large language models' ability to capture ever-changing world knowledge.

Significant efforts have been dedicated to integrating the powerful Large Language Models (LLMs) with diverse modality, particularly focusing on the fusion of language, vision...

The dataset used to evaluate the effectiveness of different jailbreak attack methods against LLMs. The dataset contains 160 forbidden questions with high diversity.

The dataset used in the paper to evaluate the effectiveness of different jailbreak attack methods against Large Language Models (LLMs).

Xiezhi comprises multiple-choice questions across 516 diverse disciplines ranging from 13 different subjects with 249,587 questions and accompanied by Xiezhi-Specialty with...