Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
ReactionT5: a large-scale pre-trained model towards application of limited reaction data
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2311.06708.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:59:26.107539Z
A source-named dated measurement, never combined with another source.
Source: pith, 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
8
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation a4df42c8-fb3b-4dc7-9d0d-0c4bb07ecc88 · inbound
ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models cites this paper.
ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models ReactionT5: a large-scale pre-trained model towards application of limited reaction data
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:59:26.107539Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 722a53a6-f24e-489d-abfc-68c9e7317a5e · inbound
Augmenting Molecular Language Models with Local $n$-gram Memory cites this paper.
Augmenting Molecular Language Models with Local $n$-gram Memory ReactionT5: a large-scale pre-trained model towards application of limited reaction data
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T10:37:56.671952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 0ad5d913-b6f6-4b78-9128-114754b17405 · inbound
Where to cut, how deep: BPE and Unigram-LM on chemistry SMILES cites this paper.
Where to cut, how deep: BPE and Unigram-LM on chemistry SMILES ReactionT5: a large-scale pre-trained model towards application of limited reaction data
Reference 40
- Resolution
- verified exact
- local_arxiv, observed 2026-07-11T03:47:46.825551Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.