Paper Citation Record · LEDGER

TAPEX: Table Pre-training via Learning a Neural SQL Executor

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2107.07653.

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

pith.paper-citation-record.v1
2107.07653 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:47:40.700778Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T09:57:56.204342Z

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 17ba75ed-0d45-4710-a91e-778e22250caf · inbound

What to Keep and What to Drop: Adaptive Table Filtering Framework cites this paper.

What to Keep and What to Drop: Adaptive Table Filtering Framework TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T21:47:40.700778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50de6d48-024b-4a36-bc2c-675945442484 · inbound

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering cites this paper.

OpenTable-R1: A Reinforcement Learning Augmented Tool Agent for Open-Domain Table Question Answering TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T20:48:15.279540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b4dacb0-5c56-4b9c-92d4-4badf7d016da · inbound

MRT at IberLEF-2025 PRESTA Task: Maximizing Recovery from Tables with Multiple Steps cites this paper.

MRT at IberLEF-2025 PRESTA Task: Maximizing Recovery from Tables with Multiple Steps TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T16:36:51.915513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 032466e9-ba86-4c9e-aa3e-529339ba4aca · inbound

TableMind: An Autonomous Programmatic Agent for Tool-Augmented Table Reasoning cites this paper.

TableMind: An Autonomous Programmatic Agent for Tool-Augmented Table Reasoning TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T23:56:52.567514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c10ea1b3-72f8-4260-bcb3-4af4ecd88852 · inbound

When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables cites this paper.

When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:40:40.872469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 17e83f1c-f9a2-4465-8f38-c9b32c83bac9 · 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 TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:21:10.707411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2bc097e8-919f-40ce-8e0f-24f18b2fba65 · inbound

RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners cites this paper.

RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:16:05.278829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c1bbf099-b7a9-42d3-aa13-3f0a5f7eea73 · inbound

TabClaw: An Interactive and Self-Evolving Agent for Spreadsheet Manipulation and Table Reasoning cites this paper.

TabClaw: An Interactive and Self-Evolving Agent for Spreadsheet Manipulation and Table Reasoning TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-03T05:07:38.935366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 50323458-9b57-4ad1-84ce-a501bd525e3f · inbound

MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning cites this paper.

MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:57:56.205994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 52b0f627-198b-4eeb-be43-44b74b528deb · inbound

SpreadsheetBench 2: Evaluating Agents on End-to-End Business Spreadsheet Workflows cites this paper.

SpreadsheetBench 2: Evaluating Agents on End-to-End Business Spreadsheet Workflows TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:04:45.401749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.