Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Can Large Language Models Understand Molecules?
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.00024.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:39:23.198170Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T23:20:21.872764Z
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 943a0fcc-56a3-469a-b63c-82ac7225e7ad · inbound
Leveraging neural network interatomic potentials for a foundation model of chemistry cites this paper.
Leveraging neural network interatomic potentials for a foundation model of chemistry Can Large Language Models Understand Molecules?
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T23:20:21.990649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 77675b23-0224-409a-8dca-1a430efe0fd9 · inbound
$\text{M}^{2}$LLM: Multi-view Molecular Representation Learning with Large Language Models cites this paper.
$\text{M}^{2}$LLM: Multi-view Molecular Representation Learning with Large Language Models Can Large Language Models Understand Molecules?
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:39:23.198170Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 03f799ef-aa31-4dc2-89b9-42c9a4b29ea8 · inbound
Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language cites this paper.
Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language Can Large Language Models Understand Molecules?
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:50:56.040742Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.