Paper Citation Record · LEDGER

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

As of 7 August 2026, this Paper Citation Record lists 100 of 118 outbound references and 22 inbound Pith citation observations for arXiv:2506.20920.

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

pith.paper-citation-record.v1
2506.20920 v1

Coverage vector

measured 100 of 118 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:46:42.375506Z

measured 122 of 122 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 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:16:45.263479Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

100 of 118 outbound references displayed

verified exact8
verified fuzzy2
unresolved89
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 5ec22fa5-a012-41c0-82da-f189097500a9 · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Yi: Open Foundation Models by 01.AI

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:33.435145Z

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Unavailable: canonical work link unavailable.

Observation 93645589-9dc1-4d2a-8128-c1a94669f570 · outbound

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

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:33.489072Z

Source-reported events for the cited work

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Observation 6894d93a-aa44-48df-8279-75e4b1f5b8f6 · outbound

This paper cites Llama 3 model card.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Llama 3 model card

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:33.557062Z

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Observation 9b2b22c6-7c9f-43bf-b997-1ec8c9115267 · outbound

This paper cites A survey on data selection for language models.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language A survey on data selection for language models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:33.625972Z

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Observation 767dab6a-c430-4bea-a8fa-31aa9e767aec · outbound

This paper cites Open llm turkish leaderboard v0.2.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Open llm turkish leaderboard v0.2

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:33.702254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1f05eab-e33f-40fb-977c-3aac94923944 · outbound

This paper cites A l G hafa evaluation benchmark for A rabic language models.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language A l G hafa evaluation benchmark for A rabic language models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:33.797026Z

Source-reported events for the cited work

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Observation c00582aa-05a4-47a7-96da-83d765789020 · outbound

This paper cites 101 billion arabic words dataset, 2024.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language 101 billion arabic words dataset, 2024

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:33.843819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20cce32f-fab4-43bc-8d2e-76412bc7fc45 · outbound

This paper cites On the cross-lingual transferability of monolingual representations.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language On the cross-lingual transferability of monolingual representations

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:33.881227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67eaca72-07bb-4902-b2db-fa169d3747a0 · outbound

This paper cites A call for more rigor in unsupervised cross-lingual learning.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language A call for more rigor in unsupervised cross-lingual learning

Reference 9

Resolution: verified exact; doi, observed 2026-08-06T22:46:43.869917Z

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 fd5889bf-fa8d-4af2-aa2b-5ae7d4a83975 · outbound

This paper cites Japanese massive multitask language understanding benchmark, 2023.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Japanese massive multitask language understanding benchmark, 2023

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:33.995458Z

Source-reported events for the cited work

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Observation 9b0d82cf-0d66-40f5-8a0e-da42bf5d4814 · outbound

This paper cites The belebele benchmark: a parallel reading comprehension dataset in 122 language variants.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language The belebele benchmark: a parallel reading comprehension dataset in 122 language variants

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:34.075955Z

Source-reported events for the cited work

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Observation 2d29a952-39ae-463d-87d5-d28ef38c1316 · outbound

This paper cites Building Machine Translation Systems for the Next Thousand Languages.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Building Machine Translation Systems for the Next Thousand Languages

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:34.150087Z

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Unavailable: canonical work link unavailable.

Observation aee1a052-c635-4462-b70b-a26749d0af24 · outbound

This paper cites Trafilatura: A Web Scraping Library and Command-Line Tool for Text Discovery and Extraction.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Trafilatura: A Web Scraping Library and Command-Line Tool for Text Discovery and Extraction

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:34.210423Z

Source-reported events for the cited work

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Observation c3578c5c-d4c7-49a8-a653-2ca0dfa9d86e · outbound

This paper cites On the resemblance and containment of documents.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language On the resemblance and containment of documents

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:34.319292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ead3e28e-4569-40f6-878e-666442a5ef75 · outbound

This paper cites An open dataset and model for language identification.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language An open dataset and model for language identification

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:34.474853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f6c3cb5-c38d-4cce-b6f4-f6f4b634ed5a · outbound

This paper cites An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT).

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:34.583082Z

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Observation 51c0b978-de55-4141-810a-32a5f05bf112 · outbound

This paper cites PTT5: Pretraining and validating the T5 model on Brazilian Portuguese data.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language PTT5: Pretraining and validating the T5 model on Brazilian Portuguese data

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:34.736671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d97dbaa2-3c1b-4e30-bb53-124de1eeb969 · outbound

This paper cites Language ID in the wild: Unexpected challenges on the path to a thousand-language web text corpus.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Language ID in the wild: Unexpected challenges on the path to a thousand-language web text corpus

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:34.831748Z

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Observation f48cd5d1-bcbe-49cb-8ec9-074466a7393e · outbound

This paper cites Clark, Eunsol Choi, Michael Collins, Dan Garrette, Tom Kwiatkowski, Vitaly Nikolaev, and Jennimaria Palomaki.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Clark, Eunsol Choi, Michael Collins, Dan Garrette, Tom Kwiatkowski, Vitaly Nikolaev, and Jennimaria Palomaki

Reference 19

Resolution: malformed identifier; no resolver link, observed 2026-08-06T22:46:34.988316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a73efc9f-d303-4a64-a261-dd8ea894f2dd · outbound

This paper cites Command r+.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Command r+

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:35.082235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 204dfc02-b923-4ba9-85cb-9b4525f83964 · outbound

This paper cites Unsupervised cross-lingual representation learning at scale.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Unsupervised cross-lingual representation learning at scale

Reference 21

Resolution: verified exact; doi, observed 2026-08-06T22:46:43.742969Z

Source-reported events for the cited work

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Observation ebfebb77-afd4-4762-8ae6-1ec465b2ef68 · outbound

This paper cites Neural learning for question answering in italian.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Neural learning for question answering in italian

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:35.333775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df62415c-318d-40c7-80cc-884a41aa911f · outbound

This paper cites Dataset for the First Evaluation on Chinese Machine Reading Comprehension.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Dataset for the First Evaluation on Chinese Machine Reading Comprehension

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:46:45.068840Z

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 504fbcb6-49c0-4587-9919-3ba7ae8ddc77 · outbound

This paper cites Daniels and William Bright (eds.).

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Daniels and William Bright (eds.)

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:35.543260Z

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Observation 75a59b1b-7199-4d01-ba28-fac54f1e3df1 · outbound

This paper cites A New Massive Multilingual Dataset for High-Performance Language Technologies.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language A New Massive Multilingual Dataset for High-Performance Language Technologies

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:46:44.888181Z

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 ed081d84-e88a-4f48-92f3-42000a1ef7c8 · outbound

This paper cites BERTje: A Dutch BERT Model.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language BERTje: A Dutch BERT Model

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:35.817846Z

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Unavailable: canonical work link unavailable.

Observation 488d3324-dc9d-45c4-a85d-3f57bcfdbcf5 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:35.894130Z

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Observation 579cc685-a676-4f08-aa87-8aeca05345ef · outbound

This paper cites RobBERT: a Dutch RoBERTa-based Language Model.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language RobBERT: a Dutch RoBERTa-based Language Model

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:35.985633Z

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Unavailable: canonical work link unavailable.

Observation 48891c63-e204-485a-b9db-06320ce3391e · outbound

This paper cites FQuAD: French Question Answering Dataset.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language FQuAD: French Question Answering Dataset

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:46:44.741197Z

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 bf5d4220-13a8-4211-ae7c-eab29ffc1d12 · outbound

This paper cites Sailor2: Sailing in South-East Asia with Inclusive Multilingual LLMs.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Sailor2: Sailing in South-East Asia with Inclusive Multilingual LLMs

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:36.172908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96fee737-29a8-477b-b0ed-85d088c6a9fc · outbound

This paper cites Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:36.260283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3edfc52-178b-4997-99d4-9ae23425345f · outbound

This paper cites Eberhard, Gary F.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Eberhard, Gary F

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:36.357550Z

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Observation 086ea4a7-24ab-48bc-a1e0-83a70fe57691 · outbound

This paper cites SberQuAD – Russian Reading Comprehension Dataset: Description and Analysis, pp.\ 3–15.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language SberQuAD – Russian Reading Comprehension Dataset: Description and Analysis, pp.\ 3–15

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:36.484014Z

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Observation 4f6ba979-b408-4848-b114-102f4590aae4 · outbound

This paper cites Arabicweb24: Creating a high quality arabic web-only pre-training dataset, 2024.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Arabicweb24: Creating a high quality arabic web-only pre-training dataset, 2024

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:36.563221Z

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Observation 44f6f449-cb49-424c-803c-bad6e90723f9 · outbound

This paper cites Guerreiro, António Loison, Duarte M.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Guerreiro, António Loison, Duarte M

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:36.638830Z

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Observation be88cc1e-59c7-4bed-bca5-0a003eddfb9e · outbound

This paper cites MERA: A Comprehensive LLM Evaluation in Russian.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language MERA: A Comprehensive LLM Evaluation in Russian

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:36.710892Z

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Observation 4fd9627c-c59c-4bd2-9299-0f896ee29e4e · outbound

This paper cites Open llm leaderboard v2.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Open llm leaderboard v2

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:36.843320Z

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Observation fb661be8-d0a6-4bce-a8a6-859bc397a9bf · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Gemma: Open Models Based on Gemini Research and Technology

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:36.956706Z

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Unavailable: canonical work link unavailable.

Observation 981672ec-3d2a-4080-855f-8cb4f19284c7 · outbound

This paper cites The Llama 3 Herd of Models.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language The Llama 3 Herd of Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:37.083695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94c3acd5-d761-4e6b-9598-f18da8e52e00 · outbound

This paper cites Studying Large Language Model Generalization with Influence Functions.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Studying Large Language Model Generalization with Influence Functions

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:37.222530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7072c36e-25f9-4ad5-9295-6e4aa128b307 · outbound

This paper cites OLMES: A Standard for Language Model Evaluations.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language OLMES: A Standard for Language Model Evaluations

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:37.365791Z

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Unavailable: canonical work link unavailable.

Observation 9a33ca50-0ec2-4830-a8ab-8355fa9c5c2c · outbound

This paper cites EXAMS: A Multi-Subject High School Examinations Dataset for Cross-Lingual and Multilingual Question Answering.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language EXAMS: A Multi-Subject High School Examinations Dataset for Cross-Lingual and Multilingual Question Answering

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:46:44.529872Z

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 1d7babeb-2c21-4c95-8506-9831e9a7cab5 · outbound

This paper cites Measuring massive multitask language understanding.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Measuring massive multitask language understanding

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:37.613762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6cfbcb3-9399-4019-bdd0-090d0eb25307 · outbound

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Khmer natural language processing tookit

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:37.677450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59ff659f-ad21-44bc-867b-0135918901f7 · outbound

This paper cites spaCy: Industrial-strength Natural Language Processing in Python.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language spaCy: Industrial-strength Natural Language Processing in Python

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:37.821687Z

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Observation 561fdd31-a08e-42b2-bf8f-c9cb73492142 · outbound

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

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:37.938316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac51f328-e38f-40e5-8db0-f5462da4da08 · outbound

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Mistral 7B

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4ff6bd0-52bb-4dfb-9c64-fbd5f186fe61 · outbound

This paper cites Mixtral of Experts.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Mixtral of Experts

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:38.254676Z

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Unavailable: canonical work link unavailable.

Observation 1bff3b4a-7fb8-4da2-8b86-0d413dfd1696 · outbound

This paper cites The state and fate of linguistic diversity and inclusion in the NLP world.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language The state and fate of linguistic diversity and inclusion in the NLP world

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:38.411289Z

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This paper cites FastText.zip: Compressing text classification models.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language FastText.zip: Compressing text classification models

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:38.542891Z

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Unavailable: canonical work link unavailable.

Observation 0d33314e-4afd-42de-954f-636bcf10589b · outbound

This paper cites G lot LID : Language identification for low-resource languages.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language G lot LID : Language identification for low-resource languages

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:38.664452Z

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Observation f91fd40f-c527-4989-b2c1-955c2585825c · outbound

This paper cites Glot CC : An open broad-coverage commoncrawl corpus and pipeline for minority languages.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Glot CC : An open broad-coverage commoncrawl corpus and pipeline for minority languages

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:38.729060Z

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Observation ab275403-84c5-447e-86d0-96b6802e314c · outbound

This paper cites IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:38.868060Z

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Unavailable: canonical work link unavailable.

Observation bf5468c1-6200-469f-b7b6-e5dccd617073 · outbound

This paper cites Large language models only pass primary school exams in I ndonesia: A comprehensive test on I ndo MMLU.

FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Large language models only pass primary school exams in I ndonesia: A comprehensive test on I ndo MMLU

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic

Reference 56

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language The IndicNLP Library

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language JGLUE : J apanese general language understanding evaluation

Reference 58

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language F lau BERT : Unsupervised language model pre-training for F rench

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Open-arabic-llm-leaderboard-v1

Reference 61

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Deduplicating Training Data Makes Language Models Better

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Kiwipiepy: Kiwi package for python, 2024

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language MLQA: Evaluating Cross-lingual Extractive Question Answering

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language CMMLU: Measuring massive multitask language understanding in Chinese

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language DataComp-LM: In search of the next generation of training sets for language models

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Common sense beyond E nglish: Evaluating and improving multilingual language models for commonsense reasoning

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Few-shot Learning with Multilingual Language Models

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language FinGPT: Large Generative Models for a Small Language

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Quantifying Variance in Evaluation Benchmarks

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language C amem BERT : a tasty F rench language model

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Mnbvc: Massive never-ending bt vast chinese corpus

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Neural A rabic question answering

Reference 75

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Crosslingual generalization through multitask finetuning, 2022

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Rossi, and Thien Huu Nguyen

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language No Language Left Behind: Scaling Human-Centered Machine Translation

Reference 78

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Omnia russica

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Botok: State-of-the-art tokenizers for tibetan language, 2025

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Building pre-train llm dataset for the indic languages: A case study on hindi

Reference 81

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Hellaswag-th, 2023

Reference 82

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only

Reference 83

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language The fineweb datasets: Decanting the web for the finest text data at scale

Reference 84

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Laonlp: Lao language natural language processing, July 2022

Reference 85

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language P y T hai NLP : T hai natural language processing in P ython, June 2024

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Typhoon: Thai Large Language Models

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Pllum: A family of polish large language models

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Chinesesquad

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning

Reference 90

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Scaling Language Models: Methods, Analysis & Insights from Training Gopher

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 93

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Impact of Pretraining Term Frequencies on Few-Shot Reasoning

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language How Much Knowledge Can You Pack Into the Parameters of a Language Model?

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Pyidaungsu: Python library for myanmar language, 2024

Reference 97

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Compact language detector v3

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language INDIC QA BENCHMARK: A Multilingual Benchmark to Evaluate Question Answering capability of LLMs for Indic Languages

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

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FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language Thquad: Turkish historic question answering dataset for reading comprehension

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Pith citing papers

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From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

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Observation of momentum dependent charge density wave gap in EuTe4 FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

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GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

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The Effect of Scripts and Formats on LLM Numeracy FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

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A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

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OpenLID-v3: Improving the Precision of Closely Related Language Identification -- An Experience Report FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

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Scaling Laws for Mixture Pretraining Under Data Constraints FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

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Scaling Laws for Mixture Pretraining Under Data Constraints cites this paper.

Scaling Laws for Mixture Pretraining Under Data Constraints FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 34

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Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings cites this paper.

Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

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Granite Embedding Multilingual R2 Models cites this paper.

Granite Embedding Multilingual R2 Models FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 14

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A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAM$\Delta$ Integration into Upcycled MoE cites this paper.

A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAM$\Delta$ Integration into Upcycled MoE FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 24

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SomaliWeb v1: A Quality-Filtered Somali Web Corpus with a Matched Tokenizer and a Public Language-Identification Benchmark cites this paper.

SomaliWeb v1: A Quality-Filtered Somali Web Corpus with a Matched Tokenizer and a Public Language-Identification Benchmark FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:38:12.634240Z

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Multilingual Knowledge Transfer under Data Constraints via Lexical Interventions cites this paper.

Multilingual Knowledge Transfer under Data Constraints via Lexical Interventions FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:15:20.257197Z

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Observation cf0129b7-a60b-40ca-9fb4-83adcd620143 · inbound

Mimir: Large-scale Multilingual Concept Modeling cites this paper.

Mimir: Large-scale Multilingual Concept Modeling FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T11:24:38.681356Z

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Ishigaki-IDS: An Open-Weight Verifier-Aware Model for Information Delivery Specification Drafting in Building Information Modeling cites this paper.

Ishigaki-IDS: An Open-Weight Verifier-Aware Model for Information Delivery Specification Drafting in Building Information Modeling FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 25

Resolution: malformed identifier; arxiv_id, observed 2026-07-02T23:17:29.057127Z

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Grouped Query Experts: Mixture-of-Experts on GQA Self-Attention cites this paper.

Grouped Query Experts: Mixture-of-Experts on GQA Self-Attention FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:49:29.893255Z

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Observation d2bd763f-f994-4834-9947-29e54e4eb04e · inbound

moBERTo: A Modern Encoder for Portuguese via Continued Pretraining of ModernBERT cites this paper.

moBERTo: A Modern Encoder for Portuguese via Continued Pretraining of ModernBERT FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T09:19:44.124861Z

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Observation 1b5b1bdb-58fb-408b-9c29-2bf74907bb15 · inbound

LangMAP: A Language-Adaptive Approach to Tokenization cites this paper.

LangMAP: A Language-Adaptive Approach to Tokenization FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T10:49:46.653379Z

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

Observation d3e45960-722e-4f56-bb55-437ffa4ab47a · inbound

SARA: Unlocking Multilingual Knowledge in Mixture-of-Experts via Semantically Anchored Routing Alignment cites this paper.

SARA: Unlocking Multilingual Knowledge in Mixture-of-Experts via Semantically Anchored Routing Alignment FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T20:00:09.022875Z

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 65447489-0aee-4602-976e-e5023ff38cb3 · inbound

MultiHashFormer: Hash-based Generative Language Models cites this paper.

MultiHashFormer: Hash-based Generative Language Models FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-06-29T04:23:05.508816Z

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Observation a12afaeb-34ce-473a-91f9-9ad1b79e3171 · inbound

In-Place Tokenizer Expansion for Pre-trained LLMs cites this paper.

In-Place Tokenizer Expansion for Pre-trained LLMs FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T23:50:16.706422Z

Source-reported events for the cited work

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