Editable text user profiles make recommendations more controllable
_reachsumit · x · 2026-07-24
Controllable and Content-Based Recommendations
Firat Oncell and coauthors present a recommendation framework that builds editable, text-based user profiles directly from item content.
- Users can steer the model through those profiles rather than only relying on opaque embeddings.
- The approach is aimed at making recommendations more controllable and interpretable.
- The post points to the paper and code for more details.
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