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Paper Citation Record · LEDGER

TAGAL: Tabular Data Generation using Agentic LLM Methods

As of 7 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2509.04152.

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

pith.paper-citation-record.v1
2509.04152 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:23:25.237791Z

measured 27 of 27 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T01:03:52.964870Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:46:59.080619Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact0
  • verified fuzzy11
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aa5d25b6-188b-4a48-bd0d-2c1c5caeecf4 · outbound

This paper cites Language Models are Realistic Tabular Data Generators.

TAGAL: Tabular Data Generation using Agentic LLM Methods Language Models are Realistic Tabular Data Generators

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:22.430718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:22.430718Z digest=sha256:97e07948b695f9674d525bf4825f985f1343d4e215781a2ec5294d1d8e7aff8e

Observation 8425633e-bb01-4ab9-b36a-73b5a6be53bd · outbound

This paper cites Journal of artificial intelligence research16, 321–357 (2002).

TAGAL: Tabular Data Generation using Agentic LLM Methods Journal of artificial intelligence research16, 321–357 (2002)

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:28.490242Z

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=2026-08-05T10:23:22.517529Z digest=sha256:988add035fd82c322ca30d6941def55e159d717c3c7941b6925344283e0deb0f

Observation bcd4cda3-8415-4997-9f2f-dfb3f2841647 · outbound

This paper cites The Llama 3 Herd of Models.

TAGAL: Tabular Data Generation using Agentic LLM Methods The Llama 3 Herd of Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:22.623408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:22.623408Z digest=sha256:bcb06d07825bc8e23ef3c334fdde388be1f75af1879b2dc0a6666b2410724d5b

Observation 60e52f8d-8e23-4eaa-ba38-0f1c48545c15 · outbound

This paper cites TabGen-ICL: Residual-Aware In-Context Example Selection for Tabular Data Generation.

TAGAL: Tabular Data Generation using Agentic LLM Methods TabGen-ICL: Residual-Aware In-Context Example Selection for Tabular Data Generation

Reference 4

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T10:23:25.638029Z

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=2026-08-05T10:23:22.685511Z digest=sha256:976cdb41fed012a9293abe2d142b1c0ef7ac6d1f71bd6ed960b36de946634846

Observation c946ed72-5069-4421-8517-0df82b71f692 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

TAGAL: Tabular Data Generation using Agentic LLM Methods DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:22.813552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:22.813552Z digest=sha256:ddb69be6bc854662bc3bc82e035dcfdcff9a9e227b4b530de20a3998e877b685

Observation 39836410-b301-414f-aa15-6eb160a8776b · outbound

This paper cites an unresolved cited work.

TAGAL: Tabular Data Generation using Agentic LLM Methods Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-05T10:23:28.244022Z

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=2026-08-05T10:23:22.910198Z digest=sha256:93fbe932fc61dd725b857d9732350c0df63b3cbaa85ee6662c410bafd698c2ad

Observation 4cd4573a-25b1-4772-891f-1397b960f3c5 · outbound

This paper cites Neurocomputing493, 28–45 (2022).

TAGAL: Tabular Data Generation using Agentic LLM Methods Neurocomputing493, 28–45 (2022)

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:28.052248Z

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=2026-08-05T10:23:23.053499Z digest=sha256:7bff552de42df3b51cc87bcaac2e3ac9443d532fa85cf4460b4fe5028298b932

Observation 8bd5e704-512c-4692-b8cc-57748e0d4e1e · outbound

This paper cites GPT-4o System Card.

TAGAL: Tabular Data Generation using Agentic LLM Methods GPT-4o System Card

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:23.139390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:23.139390Z digest=sha256:7a2d73e66c64a9bcf3322e6aab2841e1f8016c6d94f04af188ffdcdc7419b36c

Observation 18af0dd0-7e6b-458e-b8df-d3e4c579643a · outbound

This paper cites Advances in Neural Information Processing Systems37, 31504–31542 (2025).

TAGAL: Tabular Data Generation using Agentic LLM Methods Advances in Neural Information Processing Systems37, 31504–31542 (2025)

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:27.815171Z

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=2026-08-05T10:23:23.232770Z digest=sha256:89a1b9fdd6943d059be1f53daeb261a577aa9c767f99732d6a82714299154120

Observation d1dcaadd-a6ab-4306-8214-1f1cb8e2a909 · outbound

This paper cites In: Proceedings of the 2022 ACM on interna- tional workshop on security and privacy analytics.

TAGAL: Tabular Data Generation using Agentic LLM Methods In: Proceedings of the 2022 ACM on interna- tional workshop on security and privacy analytics

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:27.671329Z

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=2026-08-05T10:23:23.378026Z digest=sha256:137a62f3100118360f285619b351fb7fc15e9f3e651f416b35a8441187b36951

Observation af6e3483-17a3-4201-9f12-a736bf25eae5 · outbound

This paper cites In: International Conference on Machine Learn- ing.

TAGAL: Tabular Data Generation using Agentic LLM Methods In: International Conference on Machine Learn- ing

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:27.454659Z

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=2026-08-05T10:23:23.441918Z digest=sha256:98fe699e116415d821a9c8f004a828bd6adfaa48c40f2f0da152f2eebed14a52

Observation 0757f694-6a91-41f2-a72a-7f1f267f9efd · outbound

This paper cites MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data.

TAGAL: Tabular Data Generation using Agentic LLM Methods MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:23.530117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:23.530117Z digest=sha256:3da1a277db42bd1bee7ee8594bc30898efd7fcf67197965996c6023889d9a00f

Observation e0163d27-ddf1-4e7d-a3d0-be1c1f29e007 · outbound

This paper cites DeepSeek-V3 Technical Report.

TAGAL: Tabular Data Generation using Agentic LLM Methods DeepSeek-V3 Technical Report

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:23.698136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:23.698136Z digest=sha256:5d993292f3401799daa8e993b21f2ce892c755705a237380e7a02e5111cb39d6

Observation 5972e247-c13d-42e9-8028-380d22ab9473 · outbound

This paper cites Advances in Neural Information Processing Systems36, 46534–46594 (2023).

TAGAL: Tabular Data Generation using Agentic LLM Methods Advances in Neural Information Processing Systems36, 46534–46594 (2023)

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:27.237725Z

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=2026-08-05T10:23:23.787498Z digest=sha256:83a71dc2b5255e77f44f9c8f8f432d32c08be5b1f0a7d222085c21809b7968c4

Observation 4a4c694b-4f1f-420d-8478-cf00b0767392 · outbound

This paper cites In: International conference on machine learning.

TAGAL: Tabular Data Generation using Agentic LLM Methods In: International conference on machine learning

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:27.022351Z

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=2026-08-05T10:23:23.872928Z digest=sha256:74b9f07b6fd3f05b9e45bbc8dae16bd2e5e2d20892ac3a5a732058d45eefc5a5

Observation 6efdc13d-a800-4ba2-8c05-9d01c567c141 · outbound

This paper cites an unresolved cited work.

TAGAL: Tabular Data Generation using Agentic LLM Methods Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-05T10:23:26.851841Z

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=2026-08-05T10:23:23.990514Z digest=sha256:6a7365f0075f081b19d823fa2b4e82628314cbe4c060f7a318a21d472bfba986

Observation 1af310a7-990d-4a64-a17d-34662307f249 · outbound

This paper cites Synthcity: facilitating innovative use cases of synthetic data in different data modalities.

TAGAL: Tabular Data Generation using Agentic LLM Methods Synthcity: facilitating innovative use cases of synthetic data in different data modalities

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:24.117960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:24.117960Z digest=sha256:25d9015808a891f78d9de9c9a513e9c136edaa384fa85bc3992f5d1d8b4516e6

Observation 57f19a54-ba51-4b1c-a0c5-56e8c19782f8 · outbound

This paper cites OpenAI blog1(8), 9 (2019).

TAGAL: Tabular Data Generation using Agentic LLM Methods OpenAI blog1(8), 9 (2019)

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:24.289063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:24.289063Z digest=sha256:d9f6655c34bedc8d159cbe8d02426d80158eeb2a4d86e62b09a532670e65b22c

Observation 93afa6aa-5832-4352-993e-60bfa0e6852f · outbound

This paper cites In: International Symposium on Intelligent Data Analysis.

TAGAL: Tabular Data Generation using Agentic LLM Methods In: International Symposium on Intelligent Data Analysis

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:26.651350Z

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=2026-08-05T10:23:24.389215Z digest=sha256:96a9e1be5f90a8fee3b42b9a4112d3a2a884c48164797a026fba3cec374c94e8

Observation 79434224-a39a-45e4-b78b-2f5f4a6a20e1 · outbound

This paper cites Advances in neural information processing systems31 (2018).

TAGAL: Tabular Data Generation using Agentic LLM Methods Advances in neural information processing systems31 (2018)

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:26.380916Z

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=2026-08-05T10:23:24.495741Z digest=sha256:4eb507f517d98695156dc24f1098c1bb1e57056f32918b3dae0360d614fc1b45

Observation 4a3f0c35-94a8-489e-8cca-188df5f5cf3a · outbound

This paper cites In: Proceedings of the Fourth ACM International Conference on AI in Finance.

TAGAL: Tabular Data Generation using Agentic LLM Methods In: Proceedings of the Fourth ACM International Conference on AI in Finance

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:26.135293Z

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=2026-08-05T10:23:24.628911Z digest=sha256:fd930594a0342c54c027dfefadd326f4f1f06353f69dcd4104484996532ef069

Observation e6addc34-b0b4-43ae-8f6c-a187ac70dca5 · outbound

This paper cites Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents.

TAGAL: Tabular Data Generation using Agentic LLM Methods Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:24.713600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:24.713600Z digest=sha256:03fc7c3f0482b914a9ee82fc714ad30cc873961d19d5281b3826cdcd2a791019

Observation 3c0e977a-5565-4bcb-a0af-22ae4460250a · outbound

This paper cites Advances in neural information processing systems35, 24824–24837 (2022).

TAGAL: Tabular Data Generation using Agentic LLM Methods Advances in neural information processing systems35, 24824–24837 (2022)

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:24.851238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:24.851238Z digest=sha256:ca311f7054e67027631045e6e7f5de829e30a39520d5561a46cabdd48037bb3a

Observation 9547e87a-a69b-4e4b-866c-ab6a1f7ef214 · outbound

This paper cites Advances in neural information processing systems32 (2019).

TAGAL: Tabular Data Generation using Agentic LLM Methods Advances in neural information processing systems32 (2019)

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:23:25.930572Z

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=2026-08-05T10:23:24.979880Z digest=sha256:c770e9a310e8841506d02c8f77fa34f1d4dd7343b6fc8d38f49c52ed6b00b15e

Observation 3aa63c6d-5bc6-4b5d-8b11-9821048a24f1 · outbound

This paper cites A Survey of Large Language Models.

TAGAL: Tabular Data Generation using Agentic LLM Methods A Survey of Large Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:25.054359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:25.054359Z digest=sha256:f279c0eff181849700938b3ba485ad9e65dd7938f3321d2a1c357f90376cd59f

Observation 131cfb29-f327-489a-91cb-af54909a7f74 · outbound

This paper cites TabuLa: Harnessing Language Models for Tabular Data Synthesis.

TAGAL: Tabular Data Generation using Agentic LLM Methods TabuLa: Harnessing Language Models for Tabular Data Synthesis

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T10:23:25.237791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:23:25.237791Z digest=sha256:c9bba85c687bccc5a5888c9fceefb3f39e98d72faa2ccf3d5a37336a2c799918

Pith citing papers

Observation e9217cc7-ee50-47bc-82a2-f9083a7fe733 · inbound

Benchmark Everything Everywhere All at Once cites this paper.

Benchmark Everything Everywhere All at Once TAGAL: Tabular Data Generation using Agentic LLM Methods

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-02T13:46:59.082147Z

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=2026-06-28T01:03:52.964870Z digest=sha256:3158670c94c8118d4241de7edb92becc6ac6a08b53e9907333703273a4df5636