Paper Citation Record · LEDGER

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

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 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 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:27:10.518899Z

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 1e0f1e0c-4897-46ec-a0e3-a43ffa29ed6a · inbound

From Words to Workflows: Automating Business Processes cites this paper.

From Words to Workflows: Automating Business Processes Large Language Models are few(1)-shot Table Reasoners

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T22:27:10.518899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c24c9736-7ee5-420e-b449-c6b3752fe414 · inbound

Improving LLM Group Fairness on Tabular Data via In-Context Learning cites this paper.

Improving LLM Group Fairness on Tabular Data via In-Context Learning Large Language Models are few(1)-shot Table Reasoners

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T21:22:42.224890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af1f6ab8-ac54-4f72-af87-61df22330c50 · inbound

Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset cites this paper.

Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset Large Language Models are few(1)-shot Table Reasoners

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T23:39:19.517744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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.

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 2026-08-21T06:32:19.484+00:00.

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.

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.

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 2026-08-21T06:32:19.484+00:00.