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Paper Citation Record · LEDGER

DARWIN Series: Domain Specific Large Language Models for Natural Science

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2308.13565.

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

pith.paper-citation-record.v1
2308.13565 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:16:35.778875Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

33
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 06271a5c-ce76-4fb9-a60f-fb2171f7e029 · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 211

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T04:32:32.973741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-23T04:30:38.804702Z digest=sha256:6bb8be13c01d2b6da419ccc33b21f90d35f666f079cac6d5a34a4b5604a22269

Observation b5447346-bd0c-432b-8df5-a6d32676b0b1 · inbound

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning cites this paper.

Toward Scientific Reasoning in LLMs: Training from Expert Discussions via Reinforcement Learning DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T14:16:35.778875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:16:35.778875Z digest=sha256:d23a05c27ae8774a11a69ab24e77552961a00576988220acd4687305a3dcc1c4

Observation 33a06a0f-d374-4ad4-ab83-7e1b6e048185 · inbound

Research on Personalized Financial Product Recommendation by Integrating Large Language Models and Graph Neural Networks cites this paper.

Research on Personalized Financial Product Recommendation by Integrating Large Language Models and Graph Neural Networks DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T10:16:54.585826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:16:54.585826Z digest=sha256:c170f4857b17b81a4a6b3f32d5a64e81af1fb90c4c2b2295580bacc0bdda2ae7

Observation 83204230-355d-4673-b5fb-e4eb908ce111 · inbound

ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge cites this paper.

ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T03:32:01.600015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T03:29:23.464348Z digest=sha256:331ea4c58175e7e859f557540b6ba003dbbcb881f7e55169d33767e145379f77

Observation 471ed568-0029-4bc3-8dea-2a381934cdce · inbound

Can Multimodal LLMs See Materials Clearly? A Multimodal Benchmark on Materials Characterization cites this paper.

Can Multimodal LLMs See Materials Clearly? A Multimodal Benchmark on Materials Characterization DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T19:25:50.075416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:25:50.075416Z digest=sha256:799ae38ebf683336d5cb2ffa85ecb93afd4faaf87aeb557594fc20afcb5f8d85

Observation 64090a04-be04-4d02-9308-648e3f2de45d · inbound

Composition-Weighted Symbolic Regression for General-Purpose Property Prediction cites this paper.

Composition-Weighted Symbolic Regression for General-Purpose Property Prediction DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:05:36.538283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T18:55:01.309563Z digest=sha256:74ee26b7fdacd6c021d72b635530751f8dc0c83126e810f38b4ee41083c17e1b

Observation 2f894438-0c85-43b0-ab14-d27ba04beb6e · inbound

Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference cites this paper.

Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-22T02:50:57.857079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-22T02:46:14.834690Z digest=sha256:b7890aa35e59838b12c9787c99aebad0c5ee4bafe47ac6bd03a4109e061312e4

Observation 0aeca14c-ec57-4bef-ae99-e3cea5b6cf8a · inbound

Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference cites this paper.

Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-25T02:55:16.119839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-25T02:51:29.233816Z digest=sha256:b18ebad4e8894888df9d243bffcde0049c00cf7ade596b1df00c6427d1d0cc96

Observation d2edc065-80c6-4c35-805d-51906ba54307 · inbound

Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference cites this paper.

Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-06-30T16:44:55.552951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-30T16:40:41.013048Z digest=sha256:5bbfe0ec4be70a4417d6a6877611e8d5c69c960cb2fc3c950d11038effa7fd89

Observation 334ce3cb-baf7-4abd-9576-c41a31a1fb18 · inbound

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines cites this paper.

From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-02T12:03:25.812895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T12:03:25.812895Z digest=sha256:0e2ec2cb985e29c23c9500053e24bafaa8f18e7d8110ffd3d9bcd825565976f4

Observation 477ef795-d829-4be5-91ff-591220125313 · inbound

Team MKC at CLPsych 2026: Capturing and Characterizing Mental Health Changes through Social Media Timeline Dynamics cites this paper.

Team MKC at CLPsych 2026: Capturing and Characterizing Mental Health Changes through Social Media Timeline Dynamics DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-01T10:05:41.581843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-07-01T05:48:29.208850Z digest=sha256:f4123259e8a1ec757d671588ca156ce9a6fdcf9fd61c3b19f95b23eec71d9e63