Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.10343.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T23:14:04.784907Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T21:42:48.261582Z
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 34d3c6c6-e134-4731-9ed6-9ae7f0155960 · inbound
Navigating Chemical-Linguistic Sharing Space with Heterogeneous Molecular Encoding cites this paper.
Navigating Chemical-Linguistic Sharing Space with Heterogeneous Molecular Encoding UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:14:04.784907Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7b9854c-9934-4f9c-b453-ac50ae8446e7 · inbound
FragmentNet: Adaptive Graph Fragmentation for Graph-to-Sequence Molecular Representation Learning cites this paper.
FragmentNet: Adaptive Graph Fragmentation for Graph-to-Sequence Molecular Representation Learning UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T16:22:47.474183Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6df6188f-2719-49dd-b176-34af23df370d · inbound
BiScale-GTR: Fragment-Aware Graph Transformers for Multi-Scale Molecular Representation Learning cites this paper.
BiScale-GTR: Fragment-Aware Graph Transformers for Multi-Scale Molecular Representation Learning UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:50:54.342071Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 4ba4032e-f267-440a-8686-70f9157d5265 · inbound
MoleCode unlocks structural intelligence in large language models cites this paper.
MoleCode unlocks structural intelligence in large language models UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T21:42:48.263601Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation cc5bf122-db00-43a4-b52c-661f83630f13 · inbound
GAE: Graph-Augmented Evolution for Scientific Discovery via Reinforcement Optimization cites this paper.
GAE: Graph-Augmented Evolution for Scientific Discovery via Reinforcement Optimization UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T14:06:35.756620Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 75e2ae4e-b8fd-4841-a105-d6792f6f62f2 · inbound
ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density cites this paper.
ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:26:38.398883Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.