Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2305.03403.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T14:45:35.444743Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
7
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 45326256-50c5-470f-a46e-7afd779d0f83 · inbound
SIFOTL: A Principled, Statistically-Informed Fidelity-Optimization Method for Tabular Learning cites this paper.
SIFOTL: A Principled, Statistically-Informed Fidelity-Optimization Method for Tabular Learning Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:45:35.444743Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7452ab75-a7b2-4021-98b5-0ecba84b1018 · inbound
Anchoring Trends: Mitigating Social Media Popularity Prediction Drift via Feature Clustering and Expansion cites this paper.
Anchoring Trends: Mitigating Social Media Popularity Prediction Drift via Feature Clustering and Expansion Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:00:10.007792Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c5bec6d2-300a-41d6-baf1-471704fef336 · inbound
In-Context Decision Making for Optimizing Complex AutoML Pipelines cites this paper.
In-Context Decision Making for Optimizing Complex AutoML Pipelines Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T22:41:53.728672Z
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.
Observation 1cd95322-5aa3-447a-9944-6de69c4c312b · inbound
Fabrication of nano-diamonds with a single NV center: Towards matter-wave interferometry with massive objects cites this paper.
Fabrication of nano-diamonds with a single NV center: Towards matter-wave interferometry with massive objects Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:59:38.298737Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9fc1590b-98ac-4879-890a-00c36691a332 · inbound
Talking Trees: Reasoning-Assisted Induction of Decision Trees for Tabular Data cites this paper.
Talking Trees: Reasoning-Assisted Induction of Decision Trees for Tabular Data Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T22:05:41.546543Z
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.
Observation efe9d4e3-0373-42a3-a2bd-bfb099f780f8 · inbound
AgentGA: Evolving Code Solutions in Agent-Seed Space cites this paper.
AgentGA: Evolving Code Solutions in Agent-Seed Space Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T12:00:20.987367Z
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.
Observation ccdf1653-4d9d-4038-bbdf-006cd751a3cc · inbound
AgentGA: Evolving Code Solutions in Agent-Seed Space cites this paper.
AgentGA: Evolving Code Solutions in Agent-Seed Space Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T04:16:20.132714Z
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.
Observation 06fb30e8-5a6f-4287-9872-b6b1d1a4de1d · inbound
Trustworthy Self-Composable Big-Data-as-a-Service: An LLM-Orchestrated Multi-Agent Framework for Automated Data Engineering, AutoML, MLOps Deployment, and Drift-Aware Lifecycle Optimization cites this paper.
Trustworthy Self-Composable Big-Data-as-a-Service: An LLM-Orchestrated Multi-Agent Framework for Automated Data Engineering, AutoML, MLOps Deployment, and Drift-Aware Lifecycle Optimization Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T23:29:02.918096Z
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.