Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Beyond designer's knowledge: Generating materials design hypotheses via large language models
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.06756.
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 2026-08-12T16:00:22.996656Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T00:25:02.429072Z
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 ea424e88-6afc-478e-b878-8d0fbb448bbc · inbound
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry cites this paper.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Beyond designer's knowledge: Generating materials design hypotheses via large language models
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.996656Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c959c75b-2bfc-46d3-aaec-8b37f1ffdb0b · inbound
AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity cites this paper.
AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity Beyond designer's knowledge: Generating materials design hypotheses via large language models
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T00:25:02.438384Z
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.