Reproduce “FairFRESH: A Neuro-Symbolic Framework for Fair and Explainable Household Food Recommendation” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Kodur Sai Vinay Sathvik, Kakoli Bora, Tejaswini R. M
FairFRESH allocates shared pantry foods among household members rather than producing separate rankings. It scores member–food pairs, assigns scarce items under a welfare rule, and filters assignments against encoded dietary rules. In 100 held-out, four-person groups simulated from survey respondents, greedy Nash allocation reduced Gini across predicted utilities from 0.192 to 0.112 and raised Recall@20 from 0.180 to 0.197; these are not observed households.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.