Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.08264.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T16:59:33.070030Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T07:33:13.935458Z
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 a9200c86-d131-4450-bcc8-af73459d48c3 · inbound
Foundational Large Language Models for Materials Research cites this paper.
Foundational Large Language Models for Materials Research MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T16:59:33.070030Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33188d1a-c76c-4c1d-b123-cadd1ba158ab · inbound
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering cites this paper.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:39:28.887635Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00e93edb-fe50-4672-a735-875aff1185d6 · inbound
MSQA: Benchmarking LLMs on Graduate-Level Materials Science Reasoning and Knowledge cites this paper.
MSQA: Benchmarking LLMs on Graduate-Level Materials Science Reasoning and Knowledge MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:43:28.439056Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ad09a9d-dfd2-45c5-8283-e3dc7ada2756 · inbound
A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools cites this paper.
A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling
Reference 156
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:45:59.901076Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ebad70a-6ef0-41a2-a253-aabca066dae9 · inbound
CrystalXRD-Bench: Benchmarking Vision-Language Models for XRD Peak Indexing Across Diverse Crystalline Materials cites this paper.
CrystalXRD-Bench: Benchmarking Vision-Language Models for XRD Peak Indexing Across Diverse Crystalline Materials MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T07:33:13.937125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.