Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1802.01483.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:30:22.787019Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T18:11:10.598432Z
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 898e22db-0104-4d4b-86ed-89407c199d5c · inbound
FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question Answering cites this paper.
FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question Answering Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:30:22.787019Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71ccf195-1757-46f5-84f6-5f6bbb6ba282 · inbound
Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data cites this paper.
Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:02:23.337927Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e1cfb1c2-e7b8-496f-9175-43841837998f · inbound
MoEcho: Exploiting Side-Channel Attacks to Compromise User Privacy in Mixture-of-Experts LLMs cites this paper.
MoEcho: Exploiting Side-Channel Attacks to Compromise User Privacy in Mixture-of-Experts LLMs Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T18:11:10.673543Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.