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Paper Citation Record · LEDGER

Large Language Models are few(1)-shot Table Reasoners

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2210.06710.

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

pith.paper-citation-record.v1
2210.06710 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:05:22.392941Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T08:52:13.698892Z

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 9eb82c22-79da-4836-8f8e-2ecca66abb2b · inbound

Large Language Models for Predictive Analysis: How Far Are They? cites this paper.

Large Language Models for Predictive Analysis: How Far Are They? Large Language Models are few(1)-shot Table Reasoners

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T15:05:22.392941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:05:22.392941Z digest=sha256:4397ad1bcb5ba8a87453931cbe4b9a852a717b153f812838a43e1c63fbbe1fe8

Observation 00b0a126-9a1b-4c19-9e08-3f8713ed46b8 · inbound

Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Models cites this paper.

Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Models Large Language Models are few(1)-shot Table Reasoners

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T06:03:42.688792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:03:42.688792Z digest=sha256:b2040a05a52812f5f18b7014d5d514302e5d45af92cb2280c46bb97c3a78fec2

Observation c8d8c4b9-59a8-478d-8733-dc5e68cd6b5d · inbound

LDI: Localized Data Imputation for Text-Rich Tables cites this paper.

LDI: Localized Data Imputation for Text-Rich Tables Large Language Models are few(1)-shot Table Reasoners

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-19T08:52:13.702814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T08:50:04.566504Z digest=sha256:662508a830a7be00506722ef8caa07cb26acf4b2b420b90723bdb17e4424ac6a

Observation f84a29a6-b34a-4b9b-bb32-f27e0e5e0f2e · inbound

Interactive Text-to-SQL via Expected Information Gain for Disambiguation cites this paper.

Interactive Text-to-SQL via Expected Information Gain for Disambiguation Large Language Models are few(1)-shot Table Reasoners

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T19:17:16.155789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:17:16.155789Z digest=sha256:fea88d4c14062e21dbda2a8abfbd46a46f5b8fe9dc32fe6cee795e137008c1e4

Observation d02229e9-c7f8-4a9e-9b42-04589fcaab6f · inbound

Development of Automated Software Design Document Review Methods Using Large Language Models cites this paper.

Development of Automated Software Design Document Review Methods Using Large Language Models Large Language Models are few(1)-shot Table Reasoners

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-04T18:26:17.836713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:26:17.836713Z digest=sha256:807dc0db3da938c47b150a713d78e3215b22383d20fa6175f54ef27f79fde5da

Observation 5b8d5881-43b9-4fbf-9e62-a87ac443fb40 · inbound

Generalizing Numerical Reasoning in Table Data through Operation Sketches and Self-Supervised Learning cites this paper.

Generalizing Numerical Reasoning in Table Data through Operation Sketches and Self-Supervised Learning Large Language Models are few(1)-shot Table Reasoners

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T14:26:02.814766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-09T21:53:51.983234Z digest=sha256:a532ff527238d70b9f20b2b2b3481d57a07ef6522e7ad003f307a40d5f9cd543