The Second Workshop on Instruction Tuning and Instruction Following

Workshop Proposal for NeurIPS 2024

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Instruction tuning has enabled modern foundation models to function beyond next-word prediction to perform a wide range of downstream tasks. This advancement has led to the creation of impactful industrial applications such as ChatGPT, Claude, and Gemini. It has also spurred increased discussion within the open-source and research communities, resulting in the creation of new benchmarks and resources, the development of new training methods, and efforts to understand the limitations of these methods. In the latest trend, we are witnessing the remarkable effectiveness of instruction-following extending beyond language only, to multi-modal settings, including advancement in applications such as image editing and robotic command execution.

To facilitate discussions on advancing instruction tuning methodologies and constructing general-purpose instruction-following models, we propose to organize the second workshop on Instruction Tuning and Instruction Following at NeurIPS 2024. It is crucial to organize this workshop due to the prevalence of proprietary models with restricted access and limited transparency regarding their training processes. This creates a pressing need for an open platform to encourage discussions and collaborations.

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