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Paper Citation Record · LEDGER

What Drives Compositional Generalization? The Importance of Continuous Training Objectives in Visual Generative Models

As of 2 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2510.03075.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2510.03075 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-02T06:30:47.504484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-10T12:39:02.545780Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-10T12:47:05.570796Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e9ad0629-5a2c-44e0-8775-6840e82abdd5 · inbound

When Do Diffusion Models learn to Generate Multiple Objects? cites this paper.

When Do Diffusion Models learn to Generate Multiple Objects? What Drives Compositional Generalization? The Importance of Continuous Training Objectives in Visual Generative Models

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-07-01T08:15:32.041741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-07-01T08:07:10.345273Z digest=sha256:03f9648e64298e1a79f4cc941b55161abadf18649dc8eb6403e04c018cea57c8

Observation 620a54c3-5b4e-4bec-900e-f9857c2b6c25 · inbound

Understanding and Mitigating the Video-Action Generalization Gap via Temporal Ratio cites this paper.

Understanding and Mitigating the Video-Action Generalization Gap via Temporal Ratio What Drives Compositional Generalization? The Importance of Continuous Training Objectives in Visual Generative Models

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-07-10T12:47:05.571985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=pdf_text observed=2026-07-10T12:39:02.545780Z digest=sha256:54fcc96dcde1faebef7663469e2eebcfbfb0ea3593889aefed07c9bf64629fac