Compositional Embeddings
Embedding approaches in which the representation of a complex object is built by combining the representations of its parts under well-defined operations, rather than learned as an opaque whole. The goal is compositionality: if you know the embedding of “red” and of “car”, you should be able to derive a meaningful representation of “red car”.
Compositionality is hard for plain point dense vectors — averaging or adding vectors is a crude proxy and loses structure. Region representations are a natural fit:
- Boxes compose via set operations — the intersection of two boxes approximates the conjunction of their concepts, giving a principled “AND”.
- This makes box/set-theoretic embeddings a concrete substrate for compositional meaning (conjunction, containment).
Note: this concept is broader than the box-embedding article that seeds it here; the link is conceptual — boxes are one well-behaved way to make embeddings compositional.
Related Concepts
- Set-Theoretic Embeddings — composition via set operations
- Box Embedding — boxes compose through intersection
- Region-Based Representation — regions support composition; points struggle
- Embeddings — point baseline where composition is only approximate
Articles
- Answering Compositional Queries with Set-Theoretic Embeddings — Shib Sankar Dasgupta et al.; box embeddings compose item–attribute relations via set operations to answer NOT queries