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Paper Citation Record · LEDGER

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models

As of 10 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 4 inbound Pith citation observations for arXiv:2502.03147.

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

pith.paper-citation-record.v1
2502.03147 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:48:07.713409Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T13:06:53.081293Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:14:25.773066Z

Reference resolution

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved13
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8b1ed376-6c97-4e6b-b4ae-27d04d2357f2 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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Observation e004fb08-d6a1-4363-8d8f-ad8d64b1516d · outbound

This paper cites an unresolved cited work.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 60c7f23b-47a9-4799-9a64-af1f737169da · outbound

This paper cites Normalized metrics compare variants where individual components of the full method (Section A.1) are removed.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Normalized metrics compare variants where individual components of the full method (Section A.1) are removed

Reference 6

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 54f5ce57-27b0-4501-8b8f-34cbfb0af464 · outbound

This paper cites Transformers Can Do Bayesian Inference.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Transformers Can Do Bayesian Inference

Reference 8

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Observation 8a60e3bd-11f2-4885-8d8f-feb54cbb83fd · outbound

This paper cites SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

Reference 9

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Observation 1a976d3d-aab2-467c-8eb3-23bcd10228ab · outbound

This paper cites an unresolved cited work.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Unresolved cited work

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c75a5024-6706-41a3-a1ff-a6369bb8ca60 · outbound

This paper cites Effective Long-Context Scaling of Foundation Models.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Effective Long-Context Scaling of Foundation Models

Reference 12

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Observation 9a830d35-f15f-45c2-8257-54a01e31f0be · outbound

This paper cites To ensure the integrity of our evaluation, we carefully filtered these datasets to eliminate any potential data contamination between the training and held-out evaluation sets.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models To ensure the integrity of our evaluation, we carefully filtered these datasets to eliminate any potential data contamination between the training and held-out evaluation sets

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e3c0058d-8e12-4945-8367-376c78a97a59 · outbound

This paper cites FTT is a widely recognized neural model for tabular learning.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models FTT is a widely recognized neural model for tabular learning

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e4b7a4c9-ac12-41a2-a15e-f0bc56ee4f56 · outbound

This paper cites Neural Baselines We evaluate three neural baselines to benchmark performance on tabular data: MLP, FT- Transformer (Gorishniy et al., 2021), and TabR (Gorishniy et al., 2024).

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Neural Baselines We evaluate three neural baselines to benchmark performance on tabular data: MLP, FT- Transformer (Gorishniy et al., 2021), and TabR (Gorishniy et al., 2024)

Reference 16

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation db1b8bfc-6834-49c7-a4d6-c022da03896b · outbound

This paper cites 123456” → “123.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models 123456” → “123

Reference 18

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 81359769-95cc-4cfb-bf28-487d88f6fe39 · outbound

This paper cites RAG-Tuned denotes results using dataset-specific retrieval methods (see Section E).

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models RAG-Tuned denotes results using dataset-specific retrieval methods (see Section E)

Reference 19

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9b5cc48e-3d9c-481c-b870-46023cab9896 · outbound

This paper cites The left figure displays the relationship between features and the label, with label values represented by point color.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models The left figure displays the relationship between features and the label, with label values represented by point color

Reference 20

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation cec1b8df-33ee-4765-8bf4-9b97cb9bd0e8 · outbound

This paper cites an unresolved cited work.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Unresolved cited work

Reference 21

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f536bb49-3914-43e8-952b-f9ac38400386 · outbound

This paper cites Index Dataset Abbr.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Index Dataset Abbr

Reference 128

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f4e0b145-b759-429e-878d-67436f47ffcb · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 1951

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Observation 17328f22-2ae5-45da-ab1a-cac063cc20ac · outbound

This paper cites To capture non-linear relationships, we fit decision trees to each feature and evaluate its contribution to target prediction in the context pool.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models To capture non-linear relationships, we fit decision trees to each feature and evaluate its contribution to target prediction in the context pool

Reference 2009

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation c56cf5f8-b5c9-47b5-a924-5f9e56d42d08 · outbound

This paper cites Scaling Laws for Neural Language Models.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Scaling Laws for Neural Language Models

Reference 2016

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Observation 5682e00f-6242-4384-a697-3aa452dd53ab · outbound

This paper cites Long-context LLMs Struggle with Long In-context Learning.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Long-context LLMs Struggle with Long In-context Learning

Reference 2020

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Observation 7e9562a2-4181-4bae-89e7-80c594d03b09 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 2021

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Observation 5a3a80e0-2625-4336-ae0a-827e72c1659c · outbound

This paper cites A Survey on In-context Learning.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models A Survey on In-context Learning

Reference 2022

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Observation 36a506c9-99ec-41e2-bd38-4364cce233ab · outbound

This paper cites DeepSeek-V3 Technical Report.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models DeepSeek-V3 Technical Report

Reference 2024

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Observation b111dfaa-a7e2-425c-a414-8f85aa03a8dc · outbound

This paper cites TabTransformer: Tabular Data Modeling Using Contextual Embeddings.

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models TabTransformer: Tabular Data Modeling Using Contextual Embeddings

Reference 2025

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Pith citing papers

Observation 3a837242-e486-4566-839e-124b1db37896 · inbound

MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining cites this paper.

MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models

Reference 29

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arxiv_id, observed 2026-05-18T18:11:42.691733Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 19b24e02-57f3-45c4-9a11-616cc08d900e · inbound

Algorithmic Recourse of In-Context Learning for Tabular Data cites this paper.

Algorithmic Recourse of In-Context Learning for Tabular Data Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models

Reference 47

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arxiv_id, observed 2026-06-28T23:42:50.157425Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T23:24:48.742677Z digest=sha256:67011f2f4bbbc6a31443a218f62a94bd6ecfaa2f018043dd9d17903ec734e29d

Observation c8041160-9f07-4aaa-8c3f-400fede8b0bc · inbound

Algorithmic Recourse of In-Context Learning for Tabular Data cites this paper.

Algorithmic Recourse of In-Context Learning for Tabular Data Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models

Reference 47

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Observation 60e5d6d3-1c57-42f4-8d09-b0c501d177f3 · inbound

Deterministic Decisions for High-Stakes AI. A Zero-Egress Pipeline with the Deployability of RAG and the Accuracy of Machine Learning cites this paper.

Deterministic Decisions for High-Stakes AI. A Zero-Egress Pipeline with the Deployability of RAG and the Accuracy of Machine Learning Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models

Reference 34

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arxiv_id, observed 2026-06-30T08:14:25.775065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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