Paper Citation Record · LEDGER

Enhancing LLMs via High-Knowledge Data Selection

As of 7 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2505.14070.

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

pith.paper-citation-record.v1
2505.14070 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:43:04.846398Z

measured 53 of 53 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

53 of 53 outbound references displayed

verified exact1
verified fuzzy5
unresolved47
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a74eaf21-8783-473a-a6e8-20a611ea55b7 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Enhancing LLMs via High-Knowledge Data Selection , " * write output.state after.block = add.period write newline

Reference 1

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Source-reported events for the cited work

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Observation de9173a3-8cf8-4534-a6d9-790eee4a79a2 · outbound

This paper cites write newline.

Enhancing LLMs via High-Knowledge Data Selection write newline

Reference 2

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Observation dea282dd-61b9-44bb-9d6b-a41f143b230f · outbound

This paper cites GPT-4 Technical Report.

Enhancing LLMs via High-Knowledge Data Selection GPT-4 Technical Report

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:59.426510Z

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Observation dae8452d-0891-4b6e-8f99-e09d2dee3682 · outbound

This paper cites Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws.

Enhancing LLMs via High-Knowledge Data Selection Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws

Reference 4

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Observation 0c904954-3672-488c-8344-c9647082f6e5 · outbound

This paper cites an unresolved cited work.

Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 5

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Observation e98dc18b-d567-41d8-bb92-b9358dc1bcf6 · outbound

This paper cites D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al.

Enhancing LLMs via High-Knowledge Data Selection D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al

Reference 6

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Observation 77d66440-fb24-4feb-971f-ed412cf8d90a · outbound

This paper cites InternLM2 Technical Report.

Enhancing LLMs via High-Knowledge Data Selection InternLM2 Technical Report

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:59.855294Z

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Observation 0c81c93e-7710-46ac-a2c9-d6889e74cde4 · outbound

This paper cites W.; Sutton, C.; Gehrmann, S.; et al.

Enhancing LLMs via High-Knowledge Data Selection W.; Sutton, C.; Gehrmann, S.; et al

Reference 8

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Observation 4540a079-92af-4088-9db1-5f8ea201ac6a · outbound

This paper cites an unresolved cited work.

Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 9

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Observation 7ce181cf-8469-4ae6-86d1-c9aa8b206eb1 · outbound

This paper cites an unresolved cited work.

Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 10

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Observation d2a2fbe9-e970-4ed8-9961-32edd9851b99 · outbound

This paper cites an unresolved cited work.

Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 11

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Observation bdc2d005-aef0-40b1-9007-da1237be39e5 · outbound

This paper cites A Survey on In-context Learning.

Enhancing LLMs via High-Knowledge Data Selection A Survey on In-context Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:00.461370Z

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Observation a3981686-3563-44c3-accf-e9815538bd1a · outbound

This paper cites The Llama 3 Herd of Models.

Enhancing LLMs via High-Knowledge Data Selection The Llama 3 Herd of Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:00.538354Z

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Observation 9cc5d988-5440-46bb-b397-31bf1a3acbb4 · outbound

This paper cites DsDm: Model-Aware Dataset Selection with Datamodels.

Enhancing LLMs via High-Knowledge Data Selection DsDm: Model-Aware Dataset Selection with Datamodels

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:00.682538Z

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Observation 4728e35d-6899-483a-af08-9db810c0debe · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Enhancing LLMs via High-Knowledge Data Selection The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 15

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Observation 3e1c8cc5-8555-41b8-8f23-9e301889eddd · outbound

This paper cites an unresolved cited work.

Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:11.494761Z

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Observation f4cff796-064c-4289-a458-672a1fd77947 · outbound

This paper cites an unresolved cited work.

Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 17

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Observation 0014f397-4dfe-448c-afe4-32285fcf2226 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Enhancing LLMs via High-Knowledge Data Selection Measuring Massive Multitask Language Understanding

Reference 18

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Observation 6366c2eb-03db-4182-a53f-1a3780e10858 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Enhancing LLMs via High-Knowledge Data Selection Training Compute-Optimal Large Language Models

Reference 19

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Observation a0f12529-6f58-4a8a-bca3-10fc5ef34ae8 · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

Enhancing LLMs via High-Knowledge Data Selection A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 20

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Observation ad171979-523b-48c6-8f1b-e67f911f71c7 · outbound

This paper cites C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models.

Enhancing LLMs via High-Knowledge Data Selection C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:01.352243Z

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Observation 91b152bf-6224-4149-8a0d-0fc2d15fe479 · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 22

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Observation 81555b22-d2fc-4a48-a3fa-5f781b8050de · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 23

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Observation bfae39f8-0608-4960-a784-faa81715624f · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 24

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Observation 297b779f-1dcb-42d1-b39f-67b71e41f16d · outbound

This paper cites an unresolved cited work.

Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:10.172184Z

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Observation 7a59dfef-6315-4d5a-a97f-4e80db70ed38 · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 26

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Observation 06e5e715-c608-4eeb-9469-b882820327ce · outbound

This paper cites CMMLU: Measuring massive multitask language understanding in Chinese.

Enhancing LLMs via High-Knowledge Data Selection CMMLU: Measuring massive multitask language understanding in Chinese

Reference 27

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This paper cites Textbooks Are All You Need II: phi-1.5 technical report.

Enhancing LLMs via High-Knowledge Data Selection Textbooks Are All You Need II: phi-1.5 technical report

Reference 28

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Observation 41a7cba7-f4ab-45f2-87d5-26d903950700 · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 29

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Observation 6e26391d-6f50-4aec-9764-d2f88b2a4bde · outbound

This paper cites AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters.

Enhancing LLMs via High-Knowledge Data Selection AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters

Reference 30

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Observation 58768ad4-65f5-4480-8f5d-e1fd7c9863c9 · outbound

This paper cites When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale.

Enhancing LLMs via High-Knowledge Data Selection When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

Reference 31

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 32

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Observation b915ff41-63fb-4189-bfd1-7b0f4c7748dd · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 33

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Observation 193edaf2-9d06-4bed-b305-31d943d7e611 · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 34

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

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Observation 1c424ac0-1f8c-4648-be64-c83f4621142f · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 36

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Observation e122454f-aa2f-4508-bacf-0cbff24f8d7d · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 37

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Observation ccc02604-daa4-4771-9356-f4847f30df9a · outbound

This paper cites T.; and Camacho-Collados, J.

Enhancing LLMs via High-Knowledge Data Selection T.; and Camacho-Collados, J

Reference 38

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Observation a402d614-35df-4bc9-bd58-86badd34f09b · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Enhancing LLMs via High-Knowledge Data Selection Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 39

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This paper cites A.; and Gordon, A.

Enhancing LLMs via High-Knowledge Data Selection A.; and Gordon, A

Reference 40

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Observation 008d596f-f874-4fec-ae02-f2b8d97f73f7 · outbound

This paper cites How to Train Data-Efficient LLMs.

Enhancing LLMs via High-Knowledge Data Selection How to Train Data-Efficient LLMs

Reference 41

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Observation 3e97874a-b70a-4fa2-9f89-bbf429272191 · outbound

This paper cites W.; Chowdhery, A.; Le, Q.; Chi, E.; Zhou, D.; et al.

Enhancing LLMs via High-Knowledge Data Selection W.; Chowdhery, A.; Le, Q.; Chi, E.; Zhou, D.; et al

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:07.764518Z

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Observation 835b2ab2-bdc7-4468-a94a-5ff50653959f · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 43

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Observation 6b002c33-edc9-45f8-98df-7a4127c0f0e1 · outbound

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

Enhancing LLMs via High-Knowledge Data Selection Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 44

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Observation b6f99658-6016-4dcb-a565-fbf9526edc3e · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 45

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Observation f315cbc0-8d87-4f8f-81a5-ed74cc1a313f · outbound

This paper cites QuRating: Selecting High-Quality Data for Training Language Models.

Enhancing LLMs via High-Knowledge Data Selection QuRating: Selecting High-Quality Data for Training Language Models

Reference 46

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Observation e03e42be-eb94-4a0f-a1d5-07667bf31966 · outbound

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Enhancing LLMs via High-Knowledge Data Selection BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 47

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Observation f4c74935-0855-4bba-9761-8db48bea8eb6 · outbound

This paper cites M.; Pham, H.; Dong, X.; Du, N.; Liu, H.; Lu, Y.; Liang, P.

Enhancing LLMs via High-Knowledge Data Selection M.; Pham, H.; Dong, X.; Du, N.; Liu, H.; Lu, Y.; Liang, P

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:06.975386Z

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Observation bcbf2f87-91e2-4fee-9a76-472d9fc8aa1b · outbound

This paper cites M.; Santurkar, S.; Ma, T.; and Liang, P.

Enhancing LLMs via High-Knowledge Data Selection M.; Santurkar, S.; Ma, T.; and Liang, P

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:06.714625Z

Source-reported events for the cited work

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Observation a81412d3-804a-4897-92df-a78aca3ed892 · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:06.340398Z

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Observation fe812265-7d11-49e3-b993-847d3e29acdc · outbound

This paper cites FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark.

Enhancing LLMs via High-Knowledge Data Selection FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark

Reference 51

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Observation 78ce1f43-17ac-4733-ba13-0b68cccbce71 · outbound

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Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:06.050140Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 76c4d10a-decb-43f7-8cd0-48954d9eb888 · outbound

This paper cites an unresolved cited work.

Enhancing LLMs via High-Knowledge Data Selection Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:05.690013Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.