Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1708.04617.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:03:16.540845Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T14:46:18.665638Z
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 6ebb5043-ed73-4d5e-8f8e-7afcf8def497 · inbound
Action is All You Need: Dual-Flow Generative Ranking Network for Recommendation cites this paper.
Action is All You Need: Dual-Flow Generative Ranking Network for Recommendation Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:03:16.540845Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6628564-b7e4-4dbe-8779-cf5a72d36651 · inbound
DLF: Enhancing Explicit-Implicit Interaction via Dynamic Low-Order-Aware Fusion for CTR Prediction cites this paper.
DLF: Enhancing Explicit-Implicit Interaction via Dynamic Low-Order-Aware Fusion for CTR Prediction Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:22:59.216973Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7db58054-6674-4447-951f-e3106ee5e4e1 · inbound
Graph-Based Feature Augmentation for Predictive Tasks on Relational Datasets cites this paper.
Graph-Based Feature Augmentation for Predictive Tasks on Relational Datasets Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
Reference 2017
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T14:46:18.671448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2f2139ba-8fb5-4fbd-b15d-e5ea5c84cdae · inbound
SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation cites this paper.
SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T23:20:19.155467Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b38a2f74-7bbd-46da-abc2-30a9ccabe70c · inbound
SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation cites this paper.
SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T04:02:20.023774Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.