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Paper Citation Record · LEDGER

SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2401.07950.

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

pith.paper-citation-record.v1
2401.07950 v3

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 2026-08-12T06:34:41.77262+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:13:47.730161Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T19:17:18.627525Z

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 c560ca0a-0147-4d33-a565-0acdd571706e · inbound

Chimera: Improving Generalist Model with Domain-Specific Experts cites this paper.

Chimera: Improving Generalist Model with Domain-Specific Experts SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-11T20:13:47.730161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:13:47.730161Z digest=sha256:cef5390d6565f49241a0f294b102b4e55359f4114e149f0f973519faa4f8e508

Observation 3213bc30-54aa-458a-83a8-255bfdb30515 · inbound

Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges cites this paper.

Towards Scientific Discovery with Generative AI: Progress, Opportunities, and Challenges SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-11T15:00:20.221280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:00:20.221280Z digest=sha256:4c574ac2fc831bf37f75d1353d47476e3915fe0e337a80ba48bee66c2227fa17

Observation 151a1fc5-49ca-4035-b992-7690d099ef4c · inbound

Parameter-Efficient Fine-Tuning for Foundation Models cites this paper.

Parameter-Efficient Fine-Tuning for Foundation Models SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T15:38:02.887904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:38:02.887904Z digest=sha256:78709d41862117b21500a7af47d9e287918c43f155acf63ad6dcb22f15627ee5

Observation 211babb4-df74-4060-97c1-9474e746b068 · inbound

Heterogeneous Scientific Foundation Model Collaboration cites this paper.

Heterogeneous Scientific Foundation Model Collaboration SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models

Reference 70

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:56:27.134409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-07T08:50:05.980191Z digest=sha256:81ae4cc7dc8cf906219b0cba814370083283d76208c0b8e06f57a1e3976d5517

Observation 2051d478-9267-4786-b086-01d6c36de15a · inbound

MatMind: A Structure-Activity Knowledge-Driven Generative Foundation Model for Materials Science cites this paper.

MatMind: A Structure-Activity Knowledge-Driven Generative Foundation Model for Materials Science SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models

Reference 40

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T19:17:18.628856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-27T21:32:29.877356Z digest=sha256:2a77c363f587977d43948b2364527790403d318bcebd013c3fa7df7b56d245fc