Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2001.01469.
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 2026-08-06T20:47:41.948730Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T08:53:04.989608Z
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 eeb1c013-4f18-48a6-a4ea-7bd0e5d99af8 · inbound
Template-Based Schema Matching of Multi-Layout Tenancy Schedules:A Comparative Study of a Template-Based Hybrid Matcher and the ALITE Full Disjunction Model cites this paper.
Template-Based Schema Matching of Multi-Layout Tenancy Schedules:A Comparative Study of a Template-Based Hybrid Matcher and the ALITE Full Disjunction Model TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:47:41.948730Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db6b2e84-f606-454d-bcab-2068fb20cd90 · inbound
DenTab: A Dataset for Table Recognition and Visual QA on Real-World Dental Estimates cites this paper.
DenTab: A Dataset for Table Recognition and Visual QA on Real-World Dental Estimates TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:53:04.991832Z
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.