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Paper Citation Record · LEDGER

Crystalite: A Lightweight Transformer for Efficient Crystal Modeling

As of 10 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 3 inbound Pith citation observations for arXiv:2604.02270.

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

pith.paper-citation-record.v1
2604.02270 v2

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T13:53:38.194246Z

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T00:30:06.382940Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T10:29:44.417849Z

Reference resolution

2 of 2 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved1
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 059ab70d-0b7e-4208-852d-e94571531452 · outbound

This paper cites Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C.

Crystalite: A Lightweight Transformer for Efficient Crystal Modeling Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-13T13:53:38.194246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T13:53:38.194246Z digest=sha256:72e4f745399e412ee595fbd104267fed9cf545014d9d53b64ef496ae40a91222

Observation 722dc5bd-a48e-48c3-bf09-689395b641f4 · outbound

This paper cites Crystal Diffusion Variational Autoencoder for Periodic Material Generation.

Crystalite: A Lightweight Transformer for Efficient Crystal Modeling Crystal Diffusion Variational Autoencoder for Periodic Material Generation

Reference 2

Resolution
malformed identifier
no resolver link, observed 2026-07-13T13:53:38.194246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T13:53:38.194246Z digest=sha256:dc33ce2b41e88339bb97e8e0c23ebcf31108a7bf988cfa8147426424474d86f8

Pith citing papers

Observation a8258534-5325-4f0c-a181-c7e317441297 · inbound

Discovering Crystal Structure Prediction Algorithms with an AI Co-Scientist cites this paper.

Discovering Crystal Structure Prediction Algorithms with an AI Co-Scientist Crystalite: A Lightweight Transformer for Efficient Crystal Modeling

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-07-04T10:19:47.006995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T09:03:00.675456Z digest=sha256:2892dce941b02f4ccbcf418f6d3587790efab5fd4fbefd64f9726a5544cbcb8d

Observation 7238a386-3a78-47cd-904d-cf85957250ac · inbound

Substitution-Based Analysis of Structural Novelty for Generative Models of Materials cites this paper.

Substitution-Based Analysis of Structural Novelty for Generative Models of Materials Crystalite: A Lightweight Transformer for Efficient Crystal Modeling

Reference 29

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T10:29:44.419481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T08:52:45.749053Z digest=sha256:5296b37b69482efb6602e1f1028326dd72fb48872e6ccfb1f1a6a2e8b9b823c6

Observation 0cf2fa3c-2d94-4821-a305-8a63b8db6a3a · inbound

Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation cites this paper.

Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation Crystalite: A Lightweight Transformer for Efficient Crystal Modeling

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-03T00:30:06.382940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:30:06.382940Z digest=sha256:2986248cc8e838fab588d760f506d41ba39afc0770d95891271fe80c811c5255