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Paper Citation Record · LEDGER

Tackling prediction tasks in relational databases with LLMs

As of 13 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 6 inbound Pith citation observations for arXiv:2411.11829.

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

pith.paper-citation-record.v1
2411.11829 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:10:37.075797Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:25:23.389004Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T06:06:41.435500Z

Reference resolution

31 of 31 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved30
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 04fc8b0c-953b-48cc-8565-e6b9834fa700 · outbound

This paper cites online" 'onlinestring :=.

Tackling prediction tasks in relational databases with LLMs online" 'onlinestring :=

Reference 1

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Observation 76d46b62-0da9-4710-964f-e071eb89f315 · outbound

This paper cites write newline.

Tackling prediction tasks in relational databases with LLMs write newline

Reference 2

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Observation 19724dad-8d5b-4111-8346-ad2b3c66f74d · outbound

This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 3

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Observation beb503f8-3151-44ca-a566-f3e3d00cb46c · outbound

This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 4

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Observation 9e0bde9c-fbb6-486b-a421-b41757c57887 · outbound

This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 5

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Observation 4ba068b4-2c82-413f-b323-b3b8ea05b7b8 · outbound

This paper cites The Llama 3 Herd of Models.

Tackling prediction tasks in relational databases with LLMs The Llama 3 Herd of Models

Reference 6

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Observation f6e21d15-712b-4e3d-95c1-19a6afa7f693 · outbound

This paper cites TabLib: A Dataset of 627M Tables with Context.

Tackling prediction tasks in relational databases with LLMs TabLib: A Dataset of 627M Tables with Context

Reference 7

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Observation cbc4d046-8192-4413-83c3-01c56f05e0a4 · outbound

This paper cites Relational Deep Learning: Graph Representation Learning on Relational Databases.

Tackling prediction tasks in relational databases with LLMs Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 8

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Observation 1ac104c5-9336-4409-9379-19d0d8c53506 · outbound

This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 9

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Observation 1290e072-41dd-44dd-bc12-3a4141de0c0a · outbound

This paper cites Ullman, and Jennifer Widom.

Tackling prediction tasks in relational databases with LLMs Ullman, and Jennifer Widom

Reference 10

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Observation b89bdf0c-3105-4e21-a3ac-5db362c2c4f7 · outbound

This paper cites Large Scale Transfer Learning for Tabular Data via Language Modeling.

Tackling prediction tasks in relational databases with LLMs Large Scale Transfer Learning for Tabular Data via Language Modeling

Reference 11

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Observation 7a4233ba-41b1-4a2c-844d-eb87f12f9f2c · outbound

This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 12

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Observation 1b5d419e-f47a-4e46-8b0f-a5e8426a89eb · outbound

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Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 13

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This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 14

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Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 15

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Observation b08be902-8c27-4662-b0a1-75e723d0114a · outbound

This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 16

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Observation 7ded04ee-2c43-4d73-9ff0-76bd83d2150f · outbound

This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 17

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Observation 16a530de-2f4b-44ea-bc6c-14b716a620ec · outbound

This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 18

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation ffef0491-0515-4936-abaf-69037d7352d8 · outbound

This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 19

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Observation bd0a26d2-2ec9-4b9c-9c29-4f13b1ab67f1 · outbound

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Tackling prediction tasks in relational databases with LLMs Regression-aware Inference with LLMs

Reference 20

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This paper cites an unresolved cited work.

Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 21

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Observation 9c0d6ba6-b553-4e3f-a7e9-909adcd8484e · outbound

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Tackling prediction tasks in relational databases with LLMs The CTU Prague Relational Learning Repository

Reference 22

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Observation 30fc8f35-a413-4fd3-b618-69d2cb9ca1be · outbound

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Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 23

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Observation a6b3816e-8f8a-4f80-b2e6-a277a8490f0e · outbound

This paper cites RelBench: A Benchmark for Deep Learning on Relational Databases.

Tackling prediction tasks in relational databases with LLMs RelBench: A Benchmark for Deep Learning on Relational Databases

Reference 24

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Observation 55c977a2-c076-41d8-8b93-a8852f0e8f80 · outbound

This paper cites Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs.

Tackling prediction tasks in relational databases with LLMs Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs

Reference 25

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Observation 7bffe2f0-f63e-40a4-8f1a-d704c405c473 · outbound

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Tackling prediction tasks in relational databases with LLMs TabularFM: An Open Framework For Tabular Foundational Models

Reference 26

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Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 27

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Observation 03cb9576-2393-4b53-aaef-23117f45405a · outbound

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Tackling prediction tasks in relational databases with LLMs Cofca: A Step-Wise Counterfactual Multi-hop QA benchmark

Reference 28

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Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 29

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Tackling prediction tasks in relational databases with LLMs Unresolved cited work

Reference 30

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Tackling prediction tasks in relational databases with LLMs Unresolved cited work

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Pith citing papers

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RelGNN: Composite Message Passing for Relational Deep Learning cites this paper.

RelGNN: Composite Message Passing for Relational Deep Learning Tackling prediction tasks in relational databases with LLMs

Reference 39

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Observation bf7fcd3d-9450-4168-8d25-8a520b02c03e · inbound

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No Need to Train Your RDB Foundation Model Tackling prediction tasks in relational databases with LLMs

Reference 24

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RelAgent: LLM Agents as Data Scientists for Relational Learning Tackling prediction tasks in relational databases with LLMs

Reference 17

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Observation 80061069-a6e5-4cd3-9b02-09ce94d007cc · inbound

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OpenRFM: Dissecting Relational In-Context Learning Tackling prediction tasks in relational databases with LLMs

Reference 55

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Observation af9950ef-abef-43d1-89ea-bb2cb1aff26f · inbound

Parameter-Free Encoders Remain Viable for RDB Foundation Models cites this paper.

Parameter-Free Encoders Remain Viable for RDB Foundation Models Tackling prediction tasks in relational databases with LLMs

Reference 21

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Observation 5de6ce3e-af7a-4219-af07-1d4b98ae5943 · inbound

Parameter-Free Encoders Remain Viable for RDB Foundation Models cites this paper.

Parameter-Free Encoders Remain Viable for RDB Foundation Models Tackling prediction tasks in relational databases with LLMs

Reference 21

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