Spaces:
Running
Running
File size: 1,539 Bytes
f060061 7200047 f060061 2c35165 f060061 7200047 f060061 7200047 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | ---
title: Epicure Explorer
emoji: "🌶"
colorFrom: green
colorTo: red
sdk: gradio
sdk_version: 5.7.1
app_file: app.py
pinned: false
license: cc-by-4.0
short_description: Operators over the three Epicure ingredient embeddings
models:
- Kaikaku/epicure-cooc
- Kaikaku/epicure-core
- Kaikaku/epicure-chem
datasets:
- Kaikaku/epicure-corpus-resources
---
# Epicure Explorer
Interactive chef-facing demo of the three Epicure sibling ingredient embeddings (Cooc, Core, Chem). Three operator tabs:
1. **Pairings**: top-K cosine neighbours plus the closest emergent mode for any of 1,790 ingredients.
2. **Supervised SLERP**: rotate a seed toward a supervised direction (cuisine macro-region, food group, NOVA level, sensory category, USDA macro) by a continuous angle.
3. **Emergent SLERP**: rotate a seed toward an unsupervised factor-mode pole discovered via multi-seed-stable FastICA + GMM.
Paper: [Epicure: Navigating the Emergent Geometry of Food Ingredient Embeddings](https://arxiv.org/abs/2605.22391).
## Try
- Pairings, `chicken`, Cooc -> garlic, onion, black_pepper, turkey, carrot (recipe companions).
- Pairings, `chicken`, Chem -> beef, pork, cream_of_chicken_soup, buffalo_wing_sauce, peanut (chemistry peers).
- Supervised SLERP, `rice` + `cuisine:South_Asian`, 30 deg, Core -> turmeric, mustard_seed, fenugreek_seed, coriander, cumin.
- Supervised SLERP, `corn` + `cuisine:Latin_American`, 30 deg, Chem -> poblano_pepper, corn_tortilla, salsa, queso_fresco, chipotle_pepper.
Citation: Radzikowski and Chen, 2026.
|