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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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.

source=arxiv_source observed=2026-08-06T21:47:40.700778Z digest=sha256:eea227a38e9b8e10f3cf3c0766a2dd15db711d0f5308893b45bd74bcdb27b456

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.

source=pdf_text observed=2026-08-06T20:48:15.279540Z digest=sha256:1a1d5f5a542d79ef4b71d6ecd38b445af2814e2d6f5f26d3eb6a3213383b241c

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.

source=pdf_text observed=2026-08-06T16:36:51.915513Z digest=sha256:ed7d47d959f42a39968e103dc307c7809dd0244819ede4631a1071e80cb67207

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.

source=pdf_text observed=2026-08-04T23:56:52.567514Z digest=sha256:361b3878f8a0367d40a5a369100a60a76d6a2e8bc52c520a1e215c2c6d9fcf34

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-21T21:38:09.388808Z digest=sha256:bcd2c540c8a369e6bae6f601177a9d05532b81fbcf63360f3e58d0020f60be59

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T09:17:00.389716Z digest=sha256:97d795633070ae796ae227cc8ba9f9ec89c9a8605e5ca38904591746f225a1f3

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-09T20:26:56.917494Z digest=sha256:14a3e6f02ef7cf0f72e3a30f88d0d20b2a050fc6955dfa5c0e77078646b45dba

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T13:26:04.468972Z digest=sha256:1bcffd74a609a699fd1db322bc28d2f4cbfc7d1962b138adbf28ca79281d7935

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T10:17:42.831128Z digest=sha256:ebcffc94a9f71cc6721175b3a112988c0ac1da9a2b677a152f0ad2aaa59bf64c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T05:36:41.816068Z digest=sha256:5431758a6713beb3a353f5b2948c16519ec220f45c8ffcf0bc369ff2811dc2b8