Papers › Provable Compositional Generalization for Object-Centric Learning

Provable Compositional Generalization for Object-Centric Learning

9 Oct 2023arXiv:2310.05327archive 2025-07-28

Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel

Learning representations that generalize to novel compositions of known concepts is crucial for bridging the gap between human and machine perception. One prominent effort is learning object-centric representations, which are widely conjectured to enable compositional generalization. Yet, it remains unclear when this conjecture will be true, as a principled theoretical or empirical understanding of compositional generalization is lacking. In this work, we investigate when compositional generalization is guaranteed for object-centric representations through the lens of identifiability theory. We show that autoencoders that satisfy structural assumptions on the decoder and enforce encoder-decoder consistency will learn object-centric representations that provably generalize compositionally. We validate our theoretical result and highlight the practical relevance of our assumptions through experiments on synthetic image data.

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collate_fn_normalizer brendel-group/objects-compositional-generalization/src/datasets/utils.py official repository ran MIT (permissive) · 7d33f028f090984d · report
compute_relative_performance brendel-group/objects-compositional-generalization/src/identifiability_evaluation/evaluation.py official repository ran fingerprinted MIT (permissive) · b2afa78cdfd900a4 · report
hungarian_algorithm brendel-group/objects-compositional-generalization/src/identifiability_evaluation/matching.py official repository ran fingerprinted MIT (permissive) · 70d1c9fdb7ec7bdd · report
hungarian_slots_loss brendel-group/objects-compositional-generalization/src/metrics.py official repository ran MIT (permissive) · d41764f3d957a830 · report
r2_score brendel-group/objects-compositional-generalization/src/metrics.py official repository ran MIT (permissive) · aec878a7da0179b8 · report
stochastic_hungarian_algorithm brendel-group/objects-compositional-generalization/src/identifiability_evaluation/matching.py official repository ran fingerprinted MIT (permissive) · 104057979a24878a · report
categorical_loss brendel-group/objects-compositional-generalization/src/identifiability_evaluation/matching.py official repository unverified MIT (permissive) · 84d74bb02b56abeb · report
image_r2_score brendel-group/objects-compositional-generalization/src/metrics.py official repository unverified MIT (permissive) · 9b0db5db94c4144b · report

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