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Paper Citation Record · LEDGER

Language Models are Realistic Tabular Data Generators

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 43 inbound Pith citation observations for arXiv:2210.06280.

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

pith.paper-citation-record.v1
2210.06280 v2

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 43 of 43 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:46:43.518680Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:58:57.943567Z

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Outbound references

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Pith citing papers

Observation de5f8553-f7ee-4b70-a935-bf586f7e93d3 · inbound

Balancing Accuracy and Efficiency in Multi-Turn Intent Classification for LLM-Powered Dialog Systems in Production cites this paper.

Balancing Accuracy and Efficiency in Multi-Turn Intent Classification for LLM-Powered Dialog Systems in Production Language Models are Realistic Tabular Data Generators

Reference 1

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no resolver link, observed 2026-08-12T17:45:31.648348Z

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source=pdf_text observed=2026-08-12T17:45:31.648348Z digest=sha256:414c411963546c435bb966232facbc43a6fcbd19000d56eba08405bf7d242d51

Observation 393cc768-8313-494b-acea-62ac7fe24c52 · inbound

SynEHRgy: Synthesizing Mixed-Type Structured Electronic Health Records using Decoder-Only Transformers cites this paper.

SynEHRgy: Synthesizing Mixed-Type Structured Electronic Health Records using Decoder-Only Transformers Language Models are Realistic Tabular Data Generators

Reference 37

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source=pdf_text observed=2026-08-12T16:30:25.770836Z digest=sha256:5804f53c6049305ad7234553f2d138ddf8ed1fbccc5d4dabab6912762e1a32fb

Observation c61a1a31-2a45-4c63-bbb3-0b3d683b5b35 · inbound

A Survey on Human-Centric LLMs cites this paper.

A Survey on Human-Centric LLMs Language Models are Realistic Tabular Data Generators

Reference 96

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no resolver link, observed 2026-08-12T16:42:08.158696Z

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source=pdf_text observed=2026-08-12T16:42:08.158696Z digest=sha256:0de994ed82d4e9f9fb7bf580b944dc61eaba7808c04e04e8076afebfc75afed6

Observation 2212549e-98e5-49de-a926-a151e2a370a7 · inbound

SoK: Watermarking for AI-Generated Content cites this paper.

SoK: Watermarking for AI-Generated Content Language Models are Realistic Tabular Data Generators

Reference 142

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source=pdf_text observed=2026-08-12T11:13:55.041882Z digest=sha256:d9706a2f414e78d7eea3b331a265203f5f898405317858d01c7d4930fe5438e0

Observation 7786f52e-0eac-4918-9fe4-332071303b65 · inbound

A text-to-tabular approach to generate synthetic patient data using LLMs cites this paper.

A text-to-tabular approach to generate synthetic patient data using LLMs Language Models are Realistic Tabular Data Generators

Reference 11

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source=pdf_text observed=2026-08-11T20:53:46.058104Z digest=sha256:70d0d68ac6d4281ae7f6f25e87a1acfe391d2488210b04cbe83fbcec77a9e720

Observation f35927b7-0e64-4e40-8340-cbbb579ad772 · inbound

AIGT: AI Generative Table Based on Prompt cites this paper.

AIGT: AI Generative Table Based on Prompt Language Models are Realistic Tabular Data Generators

Reference 5

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source=arxiv_source observed=2026-08-11T05:05:43.381061Z digest=sha256:08d361970135ca50fea682dd66223b5844ebdebc1d05d6a3e3d015d10a658bcd

Observation a5e86a8a-e521-4f07-ac7d-bdd7a8fc7473 · inbound

Creating Artificial Students that Never Existed: Leveraging Large Language Models and CTGANs for Synthetic Data Generation cites this paper.

Creating Artificial Students that Never Existed: Leveraging Large Language Models and CTGANs for Synthetic Data Generation Language Models are Realistic Tabular Data Generators

Reference 8

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arxiv_id, observed 2026-05-23T06:05:28.007816Z

Source-reported events for the cited work

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source=pdf_text observed=2026-05-23T06:04:33.506895Z digest=sha256:4184055328380a428e8230f2525eb513834f0ba89a10102df4cd1e3f0e4eae5d

Observation eec52578-ea74-424d-8bb4-7ce2c1fa1daa · inbound

Knowledge prompt chaining for semantic modeling cites this paper.

Knowledge prompt chaining for semantic modeling Language Models are Realistic Tabular Data Generators

Reference 13

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source=pdf_text observed=2026-08-10T20:27:02.102762Z digest=sha256:b995f9a57606591431bcb260ebe8658c2c6f2dae50ef3f12dd14b04953486952

Observation c8dc122d-5a01-4d3f-8ecd-bedc0addbcdb · inbound

Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation cites this paper.

Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation Language Models are Realistic Tabular Data Generators

Reference 3

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source=pdf_text observed=2026-08-10T16:21:30.153506Z digest=sha256:6f6247361211560ec693697a4085c79b11f8d47137a25bb76a9742ebe81a38b9

Observation cec62ac7-4250-4ab8-a016-09a18c7d479d · inbound

SampleLLM: Optimizing Tabular Data Synthesis in Recommendations cites this paper.

SampleLLM: Optimizing Tabular Data Synthesis in Recommendations Language Models are Realistic Tabular Data Generators

Reference 4

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source=pdf_text observed=2026-08-10T13:48:49.880759Z digest=sha256:a3425bec89aaef5dfc1275c0ff7281393d815aa483c02208a1c4b4c69252de20

Observation e8603b13-45e3-40a8-9f62-32360c376c0a · inbound

Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation cites this paper.

Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation Language Models are Realistic Tabular Data Generators

Reference 3

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arxiv_id, observed 2026-05-23T04:15:22.821180Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-23T04:13:39.627794Z digest=sha256:b9c42af6756c02e15528ddc9d047050ad5abbd470f5f58f615cbb484eb077370

Observation e61a143b-cfb2-4b45-9742-ca710417c99d · inbound

A Case Study Exploring the Current Landscape of Synthetic Medical Record Generation with Commercial LLMs cites this paper.

A Case Study Exploring the Current Landscape of Synthetic Medical Record Generation with Commercial LLMs Language Models are Realistic Tabular Data Generators

Reference 5

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source=arxiv_source observed=2026-08-16T11:46:43.518680Z digest=sha256:38d8771f807c9f021e855db57b15e91fbc45fd69b59f91a932801edcfce16241

Observation a1baf21e-372f-42e9-a5a8-0d51b1c5e386 · inbound

A Comprehensive Survey of Synthetic Tabular Data Generation cites this paper.

A Comprehensive Survey of Synthetic Tabular Data Generation Language Models are Realistic Tabular Data Generators

Reference 79

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source=pdf_text observed=2026-08-16T11:05:26.363122Z digest=sha256:590786f4614b814888ebe7eb7802df55e6a6af28e316d6ea82a81c0b8072764d

Observation 2cf3ee2d-f7c7-4791-a807-3624c2e5cfd3 · inbound

A Design Space for the Critical Validation of LLM-Generated Tabular Data cites this paper.

A Design Space for the Critical Validation of LLM-Generated Tabular Data Language Models are Realistic Tabular Data Generators

Reference 3

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source=arxiv_source observed=2026-08-15T23:30:29.398533Z digest=sha256:cc7f8f565e36365c6c3085cc8ee5989e761d9bd2c823c5ba1f02b38f5f976757

Observation 7eea258e-ae71-437a-83d1-4b935cbb7e2f · inbound

LLMSynthor: Macro-Aligned Micro-Records Synthesis with Large Language Models cites this paper.

LLMSynthor: Macro-Aligned Micro-Records Synthesis with Large Language Models Language Models are Realistic Tabular Data Generators

Reference 31

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source=pdf_text observed=2026-08-07T15:40:00.626900Z digest=sha256:3667c61ea42063c9c639856209385189e40a64401be5416f9d2667cbfe006332

Observation 55f9830b-dfa7-4d21-8f13-fa46de9043ae · inbound

The Prompt is Mightier than the Example cites this paper.

The Prompt is Mightier than the Example Language Models are Realistic Tabular Data Generators

Reference 4

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source=pdf_text observed=2026-08-07T14:34:09.774049Z digest=sha256:f69e7eb914da5d9ff3a1c79c5ea80396114a1a85b26d49e7c4889e576ea60179

Observation 45d5f491-44c9-43cf-a3fa-5123bf39a4ca · inbound

Does Prompt Design Impact Quality of Data Imputation by LLMs? cites this paper.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Language Models are Realistic Tabular Data Generators

Reference 4

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source=arxiv_source observed=2026-08-07T10:50:50.077250Z digest=sha256:391dec9e584e4d4b22bf63dce293cecc648f5c26f3429b7330bf42cea90cb06e

Observation cdb2f15d-e0d9-4589-a18b-5728699c9709 · inbound

Synthetic Tabular Data: Methods, Attacks and Defenses cites this paper.

Synthetic Tabular Data: Methods, Attacks and Defenses Language Models are Realistic Tabular Data Generators

Reference 7

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Observation 8b79da38-81c1-42f7-905a-00ec07a62a17 · inbound

FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation cites this paper.

FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation Language Models are Realistic Tabular Data Generators

Reference 7

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source=arxiv_source observed=2026-08-15T18:41:06.329864Z digest=sha256:9706d56ef0b24cd0639a1d899df11871a330bdf52ae524ce126cef12168eaa20

Observation d416ee76-39bb-48d0-a9ee-830931e6bff3 · inbound

Automatic Demonstration Selection for LLM-based Tabular Data Classification cites this paper.

Automatic Demonstration Selection for LLM-based Tabular Data Classification Language Models are Realistic Tabular Data Generators

Reference 1

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source=pdf_text observed=2026-08-06T22:52:44.785769Z digest=sha256:2927fcd82eb751a0395902980798677974c156e33b702c659f3d7c0df6c35acc

Observation 7f2db700-692b-483a-a5ee-f2ba72ec2510 · inbound

LAKEGEN: A LLM-based Tabular Corpus Generator for Evaluating Dataset Discovery in Data Lakes cites this paper.

LAKEGEN: A LLM-based Tabular Corpus Generator for Evaluating Dataset Discovery in Data Lakes Language Models are Realistic Tabular Data Generators

Reference 44

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source=pdf_text observed=2026-08-06T19:46:42.138257Z digest=sha256:08df03b62124166217e011dfddeec5a07ecd4a04aec912d8597ee07b17d5fa73

Observation e3d87345-1908-444c-890f-66a36628f9d5 · inbound

Synthetic Tabular Data Generation: A Comparative Survey for Modern Techniques cites this paper.

Synthetic Tabular Data Generation: A Comparative Survey for Modern Techniques Language Models are Realistic Tabular Data Generators

Reference 16

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source=pdf_text observed=2026-08-06T17:12:55.830748Z digest=sha256:4d1ecf68c1125fd47d0dc18f3cbedaed26c729717f1132cc7dfe1b1e941279f7

Observation 47ebc4f0-ce5b-4f8c-97a6-1625b353953b · inbound

FASTGEN: Fast and Cost-Effective Synthetic Tabular Data Generation with LLMs cites this paper.

FASTGEN: Fast and Cost-Effective Synthetic Tabular Data Generation with LLMs Language Models are Realistic Tabular Data Generators

Reference 3

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source=pdf_text observed=2026-08-06T15:27:16.017672Z digest=sha256:da1bc0d397d8f0dc7ba3d9d0246394159e1a2fb6f71aaa2f6b6d41602d7dcc1f

Observation 860cb0de-8298-4042-9ad2-f6248ad280c4 · inbound

Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs cites this paper.

Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs Language Models are Realistic Tabular Data Generators

Reference 5

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source=pdf_text observed=2026-08-06T14:58:05.260401Z digest=sha256:cd3e193b96d94517904034929268b22dbd734326e4d1701daf467d815cc8b7fc

Observation d8f9d8f5-d705-45bd-8b95-ab6a258850e0 · inbound

Dependency-aware synthetic tabular data generation cites this paper.

Dependency-aware synthetic tabular data generation Language Models are Realistic Tabular Data Generators

Reference 25

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source=pdf_text observed=2026-08-15T18:01:47.495161Z digest=sha256:e6552705a5f433bc9266523889eb03874fa89b6434dd0b65f06506fe57789c7c

Observation b00bed98-18b0-453d-84be-feae0156aac7 · inbound

Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches cites this paper.

Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches Language Models are Realistic Tabular Data Generators

Reference 9

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source=arxiv_source observed=2026-08-05T14:21:45.474882Z digest=sha256:58d02b7f8c767618cabe1b69a271a67fdac0da7d98665372bce895f5addf236c

Observation 1396e9d5-2d71-4c0a-ba7d-91b3b105e94e · inbound

Meta-learning ecological priors from large language models explains human learning and decision making cites this paper.

Meta-learning ecological priors from large language models explains human learning and decision making Language Models are Realistic Tabular Data Generators

Reference 8

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source=pdf_text observed=2026-08-05T14:46:34.721518Z digest=sha256:4e15716a35325d83f3d9c65a9d4a54bae6b70d185c8912da2ecab819f6db1b28

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

TAGAL: Tabular Data Generation using Agentic LLM Methods cites this paper.

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

Reference 1

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source=pdf_text observed=2026-08-05T10:23:22.430718Z digest=sha256:5482301ab958902e53927d5d74f54c66e0873ccf629df8433b924de663aa1b00

Observation c9d5fe93-e36c-48d5-8151-9d56ea30127c · inbound

Ensembling Membership Inference Attacks Against Tabular Generative Models cites this paper.

Ensembling Membership Inference Attacks Against Tabular Generative Models Language Models are Realistic Tabular Data Generators

Reference 3

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source=pdf_text observed=2026-08-05T11:32:55.983111Z digest=sha256:78228670996bfb412463a244621742975f2c74c3aee9fdccfe1d44337aa7bb23

Observation 7b4b893d-6ee0-4f10-8240-41d334798fef · inbound

When Tables Leak: Attacking String Memorization in LLM-Based Tabular Data Generation cites this paper.

When Tables Leak: Attacking String Memorization in LLM-Based Tabular Data Generation Language Models are Realistic Tabular Data Generators

Reference 5

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arxiv_id, observed 2026-05-16T23:48:41.864964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-16T23:47:31.667427Z digest=sha256:447f8ef53240e790c75dcd1d953aeeafc60136e2b53ad061536ae61ae2ffd257

Observation 2a816744-71a5-4741-af54-8d72c4a8eaa8 · inbound

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data Language Models are Realistic Tabular Data Generators

Reference 18

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no resolver link, observed 2026-08-03T08:15:13.774372Z

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source=arxiv_source observed=2026-08-03T08:15:13.774372Z digest=sha256:57ef5ed3fa4c9395c81f54b96437671880b11343ea8aaa0d9a4926132458a860

Observation 198e1598-1c49-43c5-a211-6ea1b453d191 · inbound

AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectors cites this paper.

AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectors Language Models are Realistic Tabular Data Generators

Reference 6

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arxiv_id, observed 2026-05-16T10:47:45.453001Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-16T10:47:17.480722Z digest=sha256:040ccc9b29e12445a7d6de0041e888262e51bca161c3232086d8180464f3bb18

Observation cca0ce04-d377-4ab8-b716-aa4b4ba21b18 · inbound

From Noise to Order: Learning to Rank via Denoising Diffusion cites this paper.

From Noise to Order: Learning to Rank via Denoising Diffusion Language Models are Realistic Tabular Data Generators

Reference 2

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source=pdf_text observed=2026-08-03T00:10:45.622152Z digest=sha256:116a4f33e8d60a7602f2892bd78c3fd5397cdd9a9c66b4150bf1da99fa18bb0e

Observation 07c17369-5c35-4734-bf57-c6b1a7fda7c6 · inbound

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training cites this paper.

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training Language Models are Realistic Tabular Data Generators

Reference 17

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arxiv_id, observed 2026-05-11T12:46:04.005475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-10T03:04:54.146481Z digest=sha256:1bc2ffac188cfb2bfde11e637edfca19610952c516b55d02ca904fd293625777

Observation ef3038b3-3e64-466c-9f1e-77b93e7c8776 · inbound

The Power of Order: Fooling LLMs with Adversarial Table Permutations cites this paper.

The Power of Order: Fooling LLMs with Adversarial Table Permutations Language Models are Realistic Tabular Data Generators

Reference 5

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arxiv_id, observed 2026-05-11T15:36:06.373211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-09T19:39:34.361824Z digest=sha256:b9a8a857b45d983e6cdba5fe86d5ee0110b04f543cbc2ea8fcda04547a6e855d

Observation 8245051c-6c43-45ec-8896-817d2a1ceb6c · inbound

The Power of Order: Fooling LLMs with Adversarial Table Permutations cites this paper.

The Power of Order: Fooling LLMs with Adversarial Table Permutations Language Models are Realistic Tabular Data Generators

Reference 5

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arxiv_id, observed 2026-05-12T02:26:16.582448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-12T02:26:05.632437Z digest=sha256:b74929766ac77b359d85c4940d4651ccc6f048a76fc8a8c666286f1049f0866c

Observation 54b079e2-ebd9-4cd5-91da-5b44db407ae4 · inbound

Breaking the Quality-Privacy Tradeoff in Tabular Data Generation via In-Context Learning cites this paper.

Breaking the Quality-Privacy Tradeoff in Tabular Data Generation via In-Context Learning Language Models are Realistic Tabular Data Generators

Reference 4

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arxiv_id, observed 2026-05-09T06:25:45.740589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T18:28:19.160555Z digest=sha256:cdef9343492b04062245a1bcaf03959add37c9b2e20f106adcf9d6c2bb4a3058

Observation bc708191-d6dc-4706-9ff8-1939b023ca87 · inbound

LLM-Driven Performance-Space Augmentation for Meta-Learning-Based Algorithm Selection cites this paper.

LLM-Driven Performance-Space Augmentation for Meta-Learning-Based Algorithm Selection Language Models are Realistic Tabular Data Generators

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T07:06:36.751436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-12T03:43:09.565887Z digest=sha256:b2ac62b45df80ab8539f6ad213899860a675d65b25ad58d61af46c9b46b03f36

Observation 89979e99-2ce0-4f8a-9cef-5d6da19a1709 · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs Language Models are Realistic Tabular Data Generators

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:16:27.611678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-12T04:26:50.410397Z digest=sha256:9341755dc71c35830bffd7d39007d31b0d152deef5ce52034bd64fbf7b46b1fd

Observation d76242ae-869d-4e66-b080-378097e83ebb · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs Language Models are Realistic Tabular Data Generators

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:23:47.865667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T22:21:03.637418Z digest=sha256:5f72af308688a3ce3ae4ea748acd5e632675eff4002f66f32e0b692613b0de4e

Observation ba801b89-df7c-4f3b-838e-9f3d8fcba110 · inbound

Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data cites this paper.

Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data Language Models are Realistic Tabular Data Generators

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:07:56.182665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T10:14:07.904158Z digest=sha256:daa0d7ae5a134f2e28c96bcb91c0eca0e41eae27f78321d077ddf854d1885ed2

Observation c7206674-345c-4048-baa8-6ffb09d183bb · inbound

PSyGenTAB: A Privacy-Preserving Framework for Synthetic Clinical Tabular Data Generation via Constrained Optimization cites this paper.

PSyGenTAB: A Privacy-Preserving Framework for Synthetic Clinical Tabular Data Generation via Constrained Optimization Language Models are Realistic Tabular Data Generators

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-03T20:58:57.945809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T01:00:26.891869Z digest=sha256:119adec7dbe7a797f4b8817acf41d85791c40a759ed53550e297935125e763f9

Observation 687d6087-fa36-46ae-857d-e440169a8214 · inbound

FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents cites this paper.

FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents Language Models are Realistic Tabular Data Generators

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-03T16:50:34.480982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T16:50:34.480982Z digest=sha256:28046ac72370bc6a93f0ca663b3e1b0abd16a8d1d9557254baf1b15231fab47c