32 datasets found

The paper investigates using a Large Language Model (LLM) to automatically perform web software tasks using click, scroll, and text input operations.

A large language model that is significantly larger than the largest model tested in the results discussed above.

The paper presents a study on the impact of synthetic data on large language models (LLMs) and proposes a method to steer LLMs towards desirable non-differentiable attributes.

A tool for collecting traces from any Python codebase that uses OpenAI’s API.

A dataset of traces from the MACHIAVELLI environment, including API calls and their outcomes.

A structured collection of tests for input-output safeguards, including established failure tests, emerging failure tests, and next-gen architecture tests.

The dataset used in this paper for digital forensic investigation using Large Language Models (LLMs).

The dataset used in the paper is a synthetic workload, where clients send requests with different input and output lengths, and with varying request rates.

The dataset used in this study to explore the ethical issues surrounding Large Language Models (LLMs).

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.