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Despite advancements in conversational AI, language models encounterchallenges to handle diverse conversational tasks, and existing dialoguedataset collections often lack diversity and comprehensiveness. To tackle theseissues, we introduce DialogStudio: the largest and most diverse collection ofdialogue datasets, unified under a consistent format while preserving theiroriginal information. Our collection encompasses data from open-domaindialogues, task-oriented dialogues, natural language understanding,conversational recommendation, dialogue summarization, and knowledge-groundeddialogues, making it an incredibly rich and diverse resource for dialogueresearch and model training. To further enhance the utility of DialogStudio, weidentify the licenses for each dataset and design domain-aware prompts forselected dialogues to facilitate instruction-aware fine-tuning. Furthermore, wedevelop conversational AI models using the dataset collection, and ourexperiments in both zero-shot and few-shot learning scenarios demonstrate thesuperiority of DialogStudio. To improve transparency and support dataset andtask-based research, as well as language model pre-training, all datasets,licenses, codes, and models associated with DialogStudio are made publiclyaccessible at https://github.com/salesforce/DialogStudio

DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI