Pith. sign in

Paper Citation Record · LEDGER

Large Language Models as Data Preprocessors

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2308.16361.

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

pith.paper-citation-record.v1
2308.16361 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:42:08.147394Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:50:11.322431Z

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 514bf400-6146-4bdd-9bac-6a366e85792d · inbound

A Survey on Human-Centric LLMs cites this paper.

A Survey on Human-Centric LLMs Large Language Models as Data Preprocessors

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-12T16:42:08.147394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:42:08.147394Z digest=sha256:8f2a8511b6ac1f9c2a0c55a11354f913f1fa662b726f19bc47aac0a1da331a41

Observation a9e23996-9404-4c62-b329-8d8199a3c414 · inbound

A Novel Approach to Balance Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes and its Implementation in BEACON cites this paper.

A Novel Approach to Balance Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes and its Implementation in BEACON Large Language Models as Data Preprocessors

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T05:11:32.524949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:11:32.524949Z digest=sha256:36453fb6ae60b6a09f130784917058ef2c91cf3d263cdaaddea89208db473f3c

Observation 570b7e98-42f5-41d3-bf0d-a415be329b90 · inbound

On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing cites this paper.

On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing Large Language Models as Data Preprocessors

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-10T22:20:28.001064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:20:28.001064Z digest=sha256:662c72485157921e111acaf68ca157424a5b3c2cc0058da332224bc69805c57b

Observation 84df6ce1-b464-46c9-ab56-4872ecc75f9a · inbound

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards cites this paper.

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards Large Language Models as Data Preprocessors

Reference 219

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:46:37.029813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-22T13:45:28.789452Z digest=sha256:54100b4066708ef19991b6b500968d943c5025798dc15a1a5b0c6155ea4d0809

Observation b0acda1d-7d58-4d78-9ddf-17c262a2e433 · inbound

Large Language Models for Predictive Analysis: How Far Are They? cites this paper.

Large Language Models for Predictive Analysis: How Far Are They? Large Language Models as Data Preprocessors

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T15:05:26.085479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:05:26.085479Z digest=sha256:d0bb15e94b0ac653e2a8f73b1ff6f3e1b13a48a3f946a4b6d35b96e97e468070

Observation 4a36521d-8c83-42eb-85dc-8073c63c1d49 · inbound

Towards Scalable Schema Mapping using Large Language Models cites this paper.

Towards Scalable Schema Mapping using Large Language Models Large Language Models as Data Preprocessors

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T12:19:35.211210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:19:35.211210Z digest=sha256:b311fc823ae82f4b4c27b5cf80f3e5c801dc720715c0f86c186f3b153311de3d

Observation 167ab8dd-bad4-450b-9ae0-7a8b773e333e · inbound

Accelerating Reinforcement Learning Algorithms Convergence using Pre-trained Large Language Models as Tutors With Advice Reusing cites this paper.

Accelerating Reinforcement Learning Algorithms Convergence using Pre-trained Large Language Models as Tutors With Advice Reusing Large Language Models as Data Preprocessors

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-04T20:49:37.811300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:49:37.811300Z digest=sha256:ead7740998c0c5b5a1f36d98d6a953a168eb185d417792ebc7dc4d808df11eb1

Observation 9196a587-78f6-4616-846c-f88a41b21907 · inbound

When control meets large language models: From words to dynamics cites this paper.

When control meets large language models: From words to dynamics Large Language Models as Data Preprocessors

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-21T14:54:13.040098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-21T14:52:44.632671Z digest=sha256:48d7d8057b95f8563fd4005fa6bde7f57ca6c262eefe08d817efe36b37dffaca

Observation 6aae2ee3-93c4-4d84-9479-5824d790acc2 · inbound

Adaptive Graph Refinement and Label Propagation with LLMs for Cost-Effective Entity Resolution cites this paper.

Adaptive Graph Refinement and Label Propagation with LLMs for Cost-Effective Entity Resolution Large Language Models as Data Preprocessors

Reference 72

Resolution
verified exact
arxiv_id, observed 2026-06-29T21:33:59.185741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-29T21:29:46.707325Z digest=sha256:6a1c7a1ec3f3d6891859ece04c3aa78f37f44e0df0dd0a26b131716130223460

Observation 3bba9e4c-48ee-4b3b-b4f4-ed2529551e40 · inbound

FlowPipe: LLM-Enhanced Conditional Generative Flow Networks for Data Preparation Pipeline Construction cites this paper.

FlowPipe: LLM-Enhanced Conditional Generative Flow Networks for Data Preparation Pipeline Construction Large Language Models as Data Preprocessors

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:49:57.512548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T00:14:25.031718Z digest=sha256:bede7b9a8496b39ce12fc1862a9df6f6dbd34beb0a452772f0310463cfd387ea

Observation efb52754-627d-4a69-b6fd-023125d18263 · inbound

TabClean: Reusable LLM-Synthesized Programs for Tabular Data Cleaning cites this paper.

TabClean: Reusable LLM-Synthesized Programs for Tabular Data Cleaning Large Language Models as Data Preprocessors

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-04T20:50:11.324089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-25T19:35:06.090910Z digest=sha256:8dceffc841c5bedc073fc445ec6800ea6b135175f5b5f2cb9b6519d95155794c