Summary of Beacon: Balancing Convenience and Nutrition in Meals with Long-term Group Recommendations and Reasoning on Multimodal Recipes, by Vansh Nagpal et al.
BEACON: Balancing Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes
by Vansh Nagpal, Siva Likitha Valluru, Kausik Lakkaraju, Biplav Srivastava
First submitted to arxiv on: 19 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a data-driven approach for meal recommendation that balances nutritional value and convenience. The authors propose a novel problem formulation that takes into account food constituents and cooking processes. They also introduce a goodness measure, recipe conversion method from text to multimodal rich recipe representation (R3) format, and learning methods using contextual bandits. These contributions show promising results. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about helping people choose what to eat for meals like breakfast, lunch, or dinner. It’s hard because we have to balance choosing healthy food with having time and liking the taste. The researchers developed a new way to suggest meals that considers both healthiness and convenience. They also came up with ways to measure how good a meal is and convert recipes from text to a special format. |
