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Paper Citation Record · LEDGER

CABINET: Content Relevance based Noise Reduction for Table Question Answering

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.01155.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2402.01155 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:22:50.845445Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-18T09:21:10.713826Z

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 7f2443df-323a-4fd6-aba3-f253945c9f43 · inbound

Utilizing Training Data to Improve LLM Reasoning for Tabular Understanding cites this paper.

Utilizing Training Data to Improve LLM Reasoning for Tabular Understanding CABINET: Content Relevance based Noise Reduction for Table Question Answering

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:50.845445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:50.845445Z digest=sha256:80ed3989274dbfc9a1febcd9b82c6b1ba230a1265b4583d5a25f82e08c564490

Observation ebaa617a-c522-496d-90fc-81f9408e84d6 · inbound

Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation cites this paper.

Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation CABINET: Content Relevance based Noise Reduction for Table Question Answering

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-18T09:21:10.716104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-18T09:17:00.389716Z digest=sha256:77f45992726b9e9babb58527a71ad2645aab2241143150775b97c9239a1cd68c