Pith. sign in

REVIEW 1 cited by

R-SQAIR: Relational Sequential Attend, Infer, Repeat

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1910.05231 v1 pith:EPN5YOJ3 submitted 2019-10-11 cs.LG stat.ML

classification cs.LGstat.ML
keywords relationalsequentialattentioninferr-sqairattendbiascombinatorial
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Traditional sequential multi-object attention models rely on a recurrent mechanism to infer object relations. We propose a relational extension (R-SQAIR) of one such attention model (SQAIR) by endowing it with a module with strong relational inductive bias that computes in parallel pairwise interactions between inferred objects. Two recently proposed relational modules are studied on tasks of unsupervised learning from videos. We demonstrate gains over sequential relational mechanisms, also in terms of combinatorial generalization.

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. SlotPi: Physics-informed Object-centric Reasoning Models

    cs.CV 2025-06 conditional novelty 5.0 of 10

    SlotPi combines a learned Hamiltonian energy module with spatiotemporal attention to improve object-centric video prediction and visual question answering on several datasets.

Pith tools