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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:35:52.671120Z digest=sha256:c5517b29bea966d4d8a2ec2c25854250df2134f9e2423ec85a85a16194ab7e13

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:35:52.741383Z digest=sha256:d00d004fd1afb82780394185ba070d0abf118fa38abd34c3f7244370746755e8

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.

source=pdf_text observed=2026-08-06T05:35:53.256609Z digest=sha256:d87855354da0f4fc9601be254895ec2e36320e84803a06e473ce41426ac84692

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:35:52.483580Z digest=sha256:9cadb6531c66b7f5e40c59c9319ee7eb1358de40ee66de1ce7ce866bc069e494

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.

source=pdf_text observed=2026-08-06T05:35:53.498292Z digest=sha256:e3068f124a1a8821eb40877ab5b3cb36ed367e383d6f8421c35ab06be3957475

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.

source=pdf_text observed=2026-08-06T05:35:53.552617Z digest=sha256:95a5df17a8b95d19d9f957b69d51709b7875ebefd6ac8639b8bc00f4c2149e6e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:35:53.624302Z digest=sha256:f9356c36a4a79b79aecffeeb1b17fed9b8984093b252486050174a4a213131fc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:35:52.944126Z digest=sha256:7655952c62d37139cd347bec87c93f3056f1e98e4c3f07b8391ef6000c11d091

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.

source=pdf_text observed=2026-08-06T05:35:52.545238Z digest=sha256:ce246052c386bfb1748ef385f5c4e3bc514a0b2918e2be50ce2ff2287c3cde08

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.

source=pdf_text observed=2026-08-06T05:35:52.849294Z digest=sha256:f408725931ff66dd194ac5b60406b928dc782c948bd29d1f9ce4e1a154dc829f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:35:53.138552Z digest=sha256:842d9c591544b783b6ca2b341ac3f75e31954f6d7bbe88f5be27cacbb7f339f8

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.

source=pdf_text observed=2026-08-06T05:35:53.404230Z digest=sha256:12462bd3df3bc266f4704a14f8139e11efab871352f4f99a01cc0dd76509aaf6

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.

source=pdf_text observed=2026-08-06T05:35:52.398700Z digest=sha256:c12e892371f00c21ced6f0ec552f1b37db26a05a530c72cbf960dbe083b801fe

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T01:01:40.043634Z digest=sha256:41b02663d6545918355417076cca41b5b4637162ff8d911c6c82850f1e22abb9