Paper Citation Record · LEDGER

From Text to Insight: Large Language Models for Materials Science Data Extraction

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2407.16867.

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

pith.paper-citation-record.v1
2407.16867 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:41:28.069687Z

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

7
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 2ef856e5-4198-4e0c-a400-3e5cf084dc09 · inbound

Foundational Large Language Models for Materials Research cites this paper.

Foundational Large Language Models for Materials Research From Text to Insight: Large Language Models for Materials Science Data Extraction

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T16:59:32.793253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a917fc2-003c-418b-892e-8daecfe5fd02 · inbound

Language Models for Materials Discovery and Sustainability: Progress, Challenges, and Opportunities cites this paper.

Language Models for Materials Discovery and Sustainability: Progress, Challenges, and Opportunities From Text to Insight: Large Language Models for Materials Science Data Extraction

Reference 180

Resolution: unresolved; no resolver link, observed 2026-08-16T11:41:28.069687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed95211e-aa68-40d6-ac28-be102e609747 · inbound

Towards Large Language Models for Lunar Mission Planning and In Situ Resource Utilization cites this paper.

Towards Large Language Models for Lunar Mission Planning and In Situ Resource Utilization From Text to Insight: Large Language Models for Materials Science Data Extraction

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T05:47:47.474293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d5fab46-4cb7-4afc-8c41-8c50994e5c79 · inbound

Evaluating Structured Output Robustness of Small Language Models for Open Attribute-Value Extraction from Clinical Notes cites this paper.

Evaluating Structured Output Robustness of Small Language Models for Open Attribute-Value Extraction from Clinical Notes From Text to Insight: Large Language Models for Materials Science Data Extraction

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T20:47:24.947182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8eec787e-26e6-4f52-aa5d-2c9c0a745992 · inbound

MatSKRAFT: A framework for large-scale materials knowledge extraction from scientific tables cites this paper.

MatSKRAFT: A framework for large-scale materials knowledge extraction from scientific tables From Text to Insight: Large Language Models for Materials Science Data Extraction

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T15:57:47.294699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9891860-e4a9-442e-85bb-fcdd15a10167 · 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 From Text to Insight: Large Language Models for Materials Science Data Extraction

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T17:31:07.427403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7b15ecac-b033-4812-8a36-733304bf57e0 · 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 From Text to Insight: Large Language Models for Materials Science Data Extraction

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T12:03:25.652384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 167fce51-4597-42be-a386-357848d28f52 · inbound

Agentic generation of verifiable rules for deterministic, self-expanding reaction classification cites this paper.

Agentic generation of verifiable rules for deterministic, self-expanding reaction classification From Text to Insight: Large Language Models for Materials Science Data Extraction

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:26:56.222394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.