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Paper Citation Record · LEDGER

DARWIN Series: Domain Specific Large Language Models for Natural Science

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 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 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:31:52.312839Z

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-23T04:30:38.804702Z digest=sha256:5e5de9c5e412663c0edcc08bd3585e29424706ce3d1278d42d6cbdcaf5f45d2b

Observation f1cc188c-f8f4-4568-8276-1e5dbb8d2af4 · inbound

Nature Language Model: Deciphering the Language of Nature for Scientific Discovery cites this paper.

Nature Language Model: Deciphering the Language of Nature for Scientific Discovery DARWIN Series: Domain Specific Large Language Models for Natural Science

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-08T12:31:52.312839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:31:52.312839Z digest=sha256:b6efa2d9dbc2a7afc8db62da7f7c3951428a6b7704c496a4278383b2aab79160

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=sha256:9dde31a561778deff57236148b9959b1a2b950cb3de5b397491c00bf79be0787

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T03:29:23.464348Z digest=sha256:9d0217a605d84edeff52e3beb5147fded44e06ea111937ff6fe3e830b782931f

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=sha256:9de900c5c583063a64e6d27a3a69fa9b3ac5338e233ee25493e2e2a09d3a0481

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T18:55:01.309563Z digest=sha256:490592c193558030c8a3a1a709950056d315efbba2f8dec875cb1c9dbca1bfca

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-22T02:46:14.834690Z digest=sha256:76dbf4c70655972571dac7c7a52952a9a56c949dad7bd981b833eaebab93991f

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-25T02:51:29.233816Z digest=sha256:de948f4889baedabcc5c2a5e2fad7be52b08a1b8f5178ec6cf00f2fb67065e5a

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-30T16:40:41.013048Z digest=sha256:e2a0a3d35c79a4ceef49450b9078c5d893e1b711323e8d934876ea95596e3174

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:e05947d5d7ac0275f7ff5aaa077c1c77487517d61acffe18d3bc830c7d2f05a4

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-01T05:48:29.208850Z digest=sha256:9c69275295c2ebe646503b0ae3ce5b3512ea9b75d4d42c18312ce7474ca43cd9