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Paper Citation Record · LEDGER

PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.13677.

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

pith.paper-citation-record.v1
2407.13677 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:17:20.963058Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T18:06:10.485677Z

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 e35ab3ff-c3bd-470e-aad2-9471c3af838c · inbound

Learning Fine-to-Coarse Cuboid Shape Abstraction cites this paper.

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.

source=pdf_text observed=2026-08-09T14:17:20.963058Z digest=sha256:23dcbd1530f1a090ba990dd9e05938ba1720e2975709624d64f6aca8c945f59c

Observation 21382ee5-220b-44cd-b055-245fc754eef2 · inbound

OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion cites this paper.

OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T19:14:14.919262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:14:14.919262Z digest=sha256:bf60120e44a875b0bc37aecaa4bc900a13132c2ec6d5dfd3150b9b5f495f55ae

Observation a9ea9160-1cff-420f-8467-75303e709604 · inbound

Repurposing 3D Generative Model for Autoregressive Layout Generation cites this paper.

Repurposing 3D Generative Model for Autoregressive Layout Generation PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-10T08:12:26.748750Z

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.

source=pdf_text observed=2026-05-10T08:09:00.779456Z digest=sha256:fc402926f9f4219d3bd22d390bbdae4ec9fc41c4447b23c97f26ca7dbbb6b3cc

Observation 4b57d97d-cfa9-4ff0-90ca-67205e6a0113 · inbound

PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World cites this paper.

PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:06:10.545365Z

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.

source=pdf_text observed=2026-05-08T16:34:56.301081Z digest=sha256:e3095898fc82b4363377be23b756d165979b1d5108a9c2e50dff590c50404f22

Observation 1f8466ae-b234-4755-ac72-8e170f1643eb · inbound

Harnessing Generative Image Models for Training-Free Primitive Shape Abstraction cites this paper.

Harnessing Generative Image Models for Training-Free Primitive Shape Abstraction PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-11T05:41:50.671046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T05:41:50.671046Z digest=sha256:c0c7a0c5077eab9badb1a40b515f9fc36c5451acc8a12250ef514e646d1f9ea9