Paper Citation Record · LEDGER

Empowering Tabular Data Preparation with Language Models: Why and How?

As of 21 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 1 inbound Pith citation observation for arXiv:2508.01556.

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

pith.paper-citation-record.v1
2508.01556 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:35:53.624302Z

measured 14 of 14 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T01:01:40.043634Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:31:25.467433Z

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy4
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 82f8b295-38d8-4bcb-bee5-32b917ec9817 · outbound

This paper cites Prompt-Matcher: Leveraging Large Models to Reduce Uncertainty in Schema Matching Results.

Empowering Tabular Data Preparation with Language Models: Why and How? Prompt-Matcher: Leveraging Large Models to Reduce Uncertainty in Schema Matching Results

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T05:35:54.124717Z

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 a58e3898-10bb-40c7-9195-4e58c0351ff4 · outbound

This paper cites A Context-Aware Approach for Enhancing Data Imputation with Pre-trained Language Models.

Empowering Tabular Data Preparation with Language Models: Why and How? A Context-Aware Approach for Enhancing Data Imputation with Pre-trained Language Models

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T05:35:53.905619Z

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 4008ad8b-2b91-47cf-80dd-67c506c5b194 · outbound

This paper cites Scaling Laws for Neural Language Models.

Empowering Tabular Data Preparation with Language Models: Why and How? Scaling Laws for Neural Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T05:35:53.256609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f21f5757-9db6-439f-a08b-5f91d4bba8c1 · outbound

This paper cites Anthropic.

Empowering Tabular Data Preparation with Language Models: Why and How? Anthropic

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:35:55.216853Z

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 5ad2c26f-4cb4-4ab7-a314-4c13f4a4fbc5 · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Empowering Tabular Data Preparation with Language Models: Why and How? The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T05:35:53.498292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e30abb8-0297-4b3a-ac8c-ca127d29448e · outbound

This paper cites KcMF: A Knowledge-compliant Framework for Schema and Entity Matching with Fine-tuning-free LLMs.

Empowering Tabular Data Preparation with Language Models: Why and How? KcMF: A Knowledge-compliant Framework for Schema and Entity Matching with Fine-tuning-free LLMs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T05:35:53.552617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fb4d758-de1f-44eb-a13d-90a76424f5f4 · outbound

This paper cites erroneous.

Empowering Tabular Data Preparation with Language Models: Why and How? erroneous

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:35:54.362918Z

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 7de7f59f-8a1d-49fc-82d9-86d412202c79 · outbound

This paper cites Sebastian Jäger, Arndt Allhorn, and Felix Bießmann.

Empowering Tabular Data Preparation with Language Models: Why and How? Sebastian Jäger, Arndt Allhorn, and Felix Bießmann

Reference 309

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:35:54.966112Z

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 dee4ca09-22a2-4198-b5bb-1db066c0f6a6 · outbound

This paper cites Data Imputation using Large Language Model to Accelerate Recommendation System.

Empowering Tabular Data Preparation with Language Models: Why and How? Data Imputation using Large Language Model to Accelerate Recommendation System

Reference 2003

Resolution: unresolved; no resolver link, observed 2026-08-06T05:35:52.545238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce970784-0cbe-4488-8dea-30030e0621ac · outbound

This paper cites Scaling Laws for Autoregressive Generative Modeling.

Empowering Tabular Data Preparation with Language Models: Why and How? Scaling Laws for Autoregressive Generative Modeling

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T05:35:52.849294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ee14133-7f1c-4048-b4ef-da1c9e86163f · outbound

This paper cites Frontiers Big Data, 4:693674.

Empowering Tabular Data Preparation with Language Models: Why and How? Frontiers Big Data, 4:693674

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:35:54.658742Z

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 fd0aa7c0-c318-450c-a476-f9970ace6845 · outbound

This paper cites ReMatch: Retrieval Enhanced Schema Matching with LLMs.

Empowering Tabular Data Preparation with Language Models: Why and How? ReMatch: Retrieval Enhanced Schema Matching with LLMs

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T05:35:53.404230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af59da19-c13f-450e-abf8-5d3685ee8620 · outbound

This paper cites MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes.

Empowering Tabular Data Preparation with Language Models: Why and How? MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T05:35:52.398700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation dfdfb23d-4261-456b-b6b3-2848564b9c46 · inbound

PrepBench: How Far Are We from Natural-Language-Driven Data Preparation? cites this paper.

PrepBench: How Far Are We from Natural-Language-Driven Data Preparation? Empowering Tabular Data Preparation with Language Models: Why and How?

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:31:25.473624Z

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.