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Paper Citation Record · LEDGER

Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2501.10555.

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

pith.paper-citation-record.v1
2501.10555 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:29:05.567414Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T14:34:45.704430Z

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 2418821f-eb3a-4bf4-8544-ca6daffbad50 · inbound

Agentic Feature Augmentation: Unifying Selection and Generation with Teaming, Planning, and Memories cites this paper.

Agentic Feature Augmentation: Unifying Selection and Generation with Teaming, Planning, and Memories Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T15:29:05.567414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:29:05.567414Z digest=sha256:a53522dd42f30dc5baaa2e231a065a9a55ab9bc71f91c4aab80b21e2e08907e3

Observation 2f8b75a5-8396-4539-ba34-1f5b9d42dd71 · inbound

Sculpting Features from Noise: Reward-Guided Hierarchical Diffusion for Task-Optimal Feature Transformation cites this paper.

Sculpting Features from Noise: Reward-Guided Hierarchical Diffusion for Task-Optimal Feature Transformation Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:49.703098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:25:49.703098Z digest=sha256:de775027e2948d0bf5a63583574f4e7996f50e35e7412e9e548747e9b58ec0bd

Observation 6b186ec6-dba3-4ed6-94a6-891f00154eb2 · inbound

Bridging the Domain Gap in Equation Distillation with Reinforcement Feedback cites this paper.

Bridging the Domain Gap in Equation Distillation with Reinforcement Feedback Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T15:19:41.432848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:19:41.432848Z digest=sha256:1b58b5df8d17ae4cf52420ae311ec2cfe149bf95f8e5b44199802a24a219a792

Observation 1b38937d-9984-4857-8b75-0752ea2ce779 · inbound

Brownian Bridge Augmented Surrogate Simulation and Injection Planning for Geological CO$_2$ Storage cites this paper.

Brownian Bridge Augmented Surrogate Simulation and Injection Planning for Geological CO$_2$ Storage Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T15:18:57.868631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:18:57.868631Z digest=sha256:9ef11979105b37f276f20023e5dfdb8de94984678dd71d3fdb7f1b18bd312d53

Observation 67ebfffb-90c5-461f-ba58-7ea1513ed79d · inbound

LLM-ML Teaming: Integrated Symbolic Decoding and Gradient Search for Valid and Stable Generative Feature Transformation cites this paper.

LLM-ML Teaming: Integrated Symbolic Decoding and Gradient Search for Valid and Stable Generative Feature Transformation Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T05:14:57.328038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:14:57.328038Z digest=sha256:66a6f2fad532fe2db35373bdcccbdf1951d24237082a93af16ce7278512bfd6b

Observation a2726999-8d48-4c29-a8c9-2386cdd8ecf8 · inbound

Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives cites this paper.

Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-06T21:29:04.583770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:29:04.583770Z digest=sha256:ab614cdd26b2b093ea3a6d6688c386abd11da0bcc26d188815f463f0509e42a3

Observation f47c3255-a019-4ffa-93b9-a6e0a7aea4a8 · inbound

LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots cites this paper.

LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-06-30T14:34:45.705643Z

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=2026-06-30T14:26:02.158915Z digest=sha256:8af28db90835750e2375fafcc3af35a1b53b790e9420c9a37f36685b7ec91de1