Eating for a Sustainable Planet: Personalized Sustainable Diet Recommendation via Constraint-Aware Decision-Making Modeling

arXiv:2608.24274 · cs.AI · Submitted 2026-08-25 · Read on arXiv

cs.AI

Submitted: 2026-08-25

Updated: 2026-08-25

Comments: Accepted in ICML 2026, 24 pages, 7 figures

License: http://creativecommons.org/licenses/by-nc-nd/4.0/

The gist: A sustainable diet represents a multi-dimensional synergy among four essential pillars: nutrition adequacy, economic affordability, cultural acceptability, and environmental respect.

Terminology

Accuracy — 14× in this paper · explained in 1 episode
Transformer — 9× in this paper · explained in 2 episodes
Attention Mechanism — 7× in this paper · explained in 3 episodes
Ablation — 6× in this paper · explained in 1 episode
Alignment — 6× in this paper · explained in 1 episode
Embeddings — 4× in this paper · explained in 2 episodes
Ablation study — 3× in this paper · explained in 1 episode
Core — 3× in this paper · explained in 2 episodes
Mixture-of-Experts (MoE) — 3× in this paper · explained in 7 episodes
Personalization — 3× in this paper · explained in 2 episodes
Regularization — 3× in this paper · explained in 3 episodes
Representation Learning — 3× in this paper · explained in 2 episodes
Clustering — 2× in this paper · explained in 2 episodes
Consistency — 2× in this paper · explained in 3 episodes
Contrastive Learning — 2× in this paper · explained in 5 episodes
Cooperation — 2× in this paper · explained in 2 episodes
Item Coverage — 2× in this paper
Loss Function — 2× in this paper · explained in 2 episodes
Robustness — 2× in this paper · explained in 5 episodes
Self-Supervised Learning — 2× in this paper · explained in 8 episodes
Verification — 2× in this paper · explained in 2 episodes
Accountability — 1× in this paper · explained in 2 episodes
Activation Function — 1× in this paper · explained in 1 episode
Aggregation — 1× in this paper · explained in 1 episode
Benchmark — 1× in this paper · explained in 2 episodes
Exposure Bias — 1× in this paper · explained in 2 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Global Alliance for Improved Nutrition — 1× in this paper
Heterogeneous Graph — 1× in this paper · explained in 2 episodes
Knowledge Graph — 1× in this paper · explained in 7 episodes
Knowledge graphs — 1× in this paper · explained in 2 episodes
Semantic Alignment — 1× in this paper · explained in 3 episodes
Sparsity — 1× in this paper · explained in 4 episodes

Abstract

A sustainable diet represents a multi-dimensional synergy among four essential pillars: nutrition adequacy, economic affordability, cultural acceptability, and environmental respect. Despite the prevalence of population-level sustainability modeling, practical implementation relies on effective individual-level adoption. This transition is often hindered by inter-individual heterogeneity, posing a formidable challenge in aligning sustainable diet requirements with individual preferences. To address this issue, we propose a personalized sustainable diet recommendation model based on a constraint-aware decision-making mechanism, where sustainability is incorporated through learnable constraints rather than modeled as user preferences. To systematically evaluate the proposed approach, we construct a sustainable diet dataset named SusDiet with about 150k recipes, characterized by broad coverage of sustainability indicators. Experimental results on this dataset show that our method promotes more sustainable choices without compromising individual preference. This work establishes a framework for aligning individual dietary choices with planetary health, offering quantitative evidence to guide future sustainable diet interventions and policy-making for sustainable development.

Sources

Generating Personalized Recipes from Historical User Preferences

Terminology

Abstract

Sources

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