Artificial intelligence (AI) has revolutionized various aspects of our lives, including shopping, planning, and writing. Yet, when it comes to cooking, AI has struggled to follow step-by-step recipes accurately. However, researchers at the Georgia Institute of Technology’s College of Computing have recently made significant progress in this field. They have developed a dataset called ChattyChef, which utilizes natural language processing models to assist users in cooking recipes.
ChattyChef’s dataset consists of cooking dialogs that guide users through recipes. The researchers use the open-source large language model GPT-J to power ChattyChef. In their paper “Improved Instruction Ordering in Recipe-Grounded Conversation,” the researchers explore the challenges of building an AI chef using large language models. Previous attempts have failed because these models struggle to understand user intent and accurately track the progression of the recipe.
To overcome these challenges, the researchers incorporated two critical features into their model. The first feature is user intent detection, which identifies what the user wants, such as requesting the next instruction or asking about ingredient details. The second feature is instruction state tracking, which helps the model identify the specific step the user is on, achieving an impressive accuracy rate of 80%.
By combining user intent detection and instruction state tracking, ChattyChef generates the most suitable response to answer a user’s question. This approach prevents confusion and ensures that users only receive relevant parts of the recipe, avoiding unnecessary steps in the cooking process.
The ChattyChef dataset is based on highly rated WikiHow recipes with fewer than eight steps. The researchers created the dataset by crowdsourcing, where individuals acted out scenarios to determine the optimal instructions to include.
The potential applications of ChattyChef’s innovations go beyond cooking. The researchers believe this approach can be applied in other domains, such as repair manuals or software documentation.
Overall, the researchers have made significant progress in addressing the challenges of building an AI chef using large language models. With user intent detection, instruction state tracking, and optimized response generation, the ChattyChef system shows promise in accurately assisting users in cooking recipes. This research opens doors to broader applications in different domains, enhancing user experiences and simplifying complex tasks through the power of AI.
If you want to learn more about this research, you can check out the Paper and Github Link. Don’t forget to join the ML SubReddit, Discord Channel, and Email Newsletter for the latest AI research news and cool AI projects. If you have any questions or if we missed anything, feel free to email us at Asif@marktechpost.com.
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Niharika is a Technical consulting intern at Marktechpost. She is currently pursuing her B.Tech in Machine Learning, Data Science, and AI at the Indian Institute of Technology (IIT), Kharagpur. She is highly enthusiastic about these fields and stays up-to-date with the latest developments.