Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T14:17:20.963058Z
Paper Citation Record · LEDGER
Learning Fine-to-Coarse Cuboid Shape Abstraction
As of 14 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 0 inbound Pith citation observations for arXiv:2502.01855.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
3 of 3 outbound references displayed
- verified exact0
- verified fuzzy1
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 210ea2ae-9f97-44c4-92a1-86744c58bf02 · outbound
This paper cites ACM Transactions on Graphics (TOG) 38, 6 (2019).
Learning Fine-to-Coarse Cuboid Shape Abstraction ACM Transactions on Graphics (TOG) 38, 6 (2019)
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T14:17:21.028166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation e35ab3ff-c3bd-470e-aad2-9471c3af838c · outbound
This paper cites PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers.
Learning Fine-to-Coarse Cuboid Shape Abstraction PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T14:17:20.963058Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a6d0fb0b-042b-4430-91e7-b713b02e5bd6 · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
Learning Fine-to-Coarse Cuboid Shape Abstraction An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T14:17:20.952577Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.