Paper Citation Record · LEDGER

The State of Large Language Models for African Languages: Progress and Challenges

As of 18 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2506.02280.

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

pith.paper-citation-record.v1
2506.02280 v3

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:31:20.747562Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T09:37:05.659296Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

48 of 48 outbound references displayed

verified exact2
verified fuzzy17
unresolved29
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 24af49ee-07cb-4fb2-a3ce-52da0a2f089d · outbound

This paper cites Masakhaner: Named entity recognition for african languages.

The State of Large Language Models for African Languages: Progress and Challenges Masakhaner: Named entity recognition for african languages

Reference 1

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Source-reported events for the cited work

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Observation 8a87328d-07dd-4ac8-b3d0-0c9ca832541a · outbound

This paper cites Alabi, David Ifeoluwa Adelani, Marius Mosbach, and Dietrich Klakow.

The State of Large Language Models for African Languages: Progress and Challenges Alabi, David Ifeoluwa Adelani, Marius Mosbach, and Dietrich Klakow

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:21.506806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 849748bf-50e9-45db-8b50-0b4f8d56c12b · outbound

This paper cites A ra BERT : Transformer-based model for A rabic language understanding.

The State of Large Language Models for African Languages: Progress and Challenges A ra BERT : Transformer-based model for A rabic language understanding

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:21.488624Z

Source-reported events for the cited work

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Observation 56e5ad4d-bf7b-4775-a034-46aa193ca82c · outbound

This paper cites A ra GPT 2: Pre-trained transformer for A rabic language generation.

The State of Large Language Models for African Languages: Progress and Challenges A ra GPT 2: Pre-trained transformer for A rabic language generation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:21.472376Z

Source-reported events for the cited work

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Observation 759a55e5-1421-44df-baba-e9b58fe31695 · outbound

This paper cites The world's writing systems, 2024.

The State of Large Language Models for African Languages: Progress and Challenges The world's writing systems, 2024

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:21.455385Z

Source-reported events for the cited work

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Observation 87ff6b22-cb72-4a9c-9043-5d58e5d84754 · outbound

This paper cites Clark, Dan Garrette, Iulia Turc, and John Wieting.

The State of Large Language Models for African Languages: Progress and Challenges Clark, Dan Garrette, Iulia Turc, and John Wieting

Reference 6

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Source-reported events for the cited work

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Observation 1f98785a-7b38-4aa3-9011-bfd5cb1f34a7 · outbound

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

The State of Large Language Models for African Languages: Progress and Challenges Unsupervised cross-lingual representation learning at scale

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T11:31:17.131375Z

Source-reported events for the cited work

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Observation 3d40d5b4-26a0-4cfa-8130-cde6496f70a0 · outbound

This paper cites Costa-jussà, James Cross, Onur Çelebi, Maha Elbayad, Kenneth Heafield, Yan He, Elahe Kalbassi, Linlu Wang, Long Wang, Shuo Zhang, Angela Fan, et al.

The State of Large Language Models for African Languages: Progress and Challenges Costa-jussà, James Cross, Onur Çelebi, Maha Elbayad, Kenneth Heafield, Yan He, Elahe Kalbassi, Linlu Wang, Long Wang, Shuo Zhang, Angela Fan, et al

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:21.438752Z

Source-reported events for the cited work

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Observation 8b865532-6f80-4e4b-b15a-31060f38b0eb · outbound

This paper cites I ndic BART : A pre-trained model for indic natural language generation.

The State of Large Language Models for African Languages: Progress and Challenges I ndic BART : A pre-trained model for indic natural language generation

Reference 9

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Source-reported events for the cited work

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Observation eb06d123-76e1-4b6e-b83b-793b9f6b5225 · outbound

This paper cites Dai, Jonathan H.

The State of Large Language Models for African Languages: Progress and Challenges Dai, Jonathan H

Reference 10

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Source-reported events for the cited work

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Observation 85b361e1-b103-4b4d-8535-7750762f7468 · outbound

This paper cites DeepSeek-V3 Technical Report.

The State of Large Language Models for African Languages: Progress and Challenges DeepSeek-V3 Technical Report

Reference 11

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Source-reported events for the cited work

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Observation f4977833-cb77-4775-ae8b-d4f83a108af5 · outbound

This paper cites BERT : Pre-training of deep bidirectional transformers for language understanding.

The State of Large Language Models for African Languages: Progress and Challenges BERT : Pre-training of deep bidirectional transformers for language understanding

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cab97324-99d7-4dad-ba90-b3e0143a9d3a · outbound

This paper cites an unresolved cited work.

The State of Large Language Models for African Languages: Progress and Challenges Unresolved cited work

Reference 13

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Source-reported events for the cited work

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Observation 8d6450d8-c029-4405-8f80-92052358a36f · outbound

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The State of Large Language Models for African Languages: Progress and Challenges Unresolved cited work

Reference 14

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Observation ffda6658-4dcf-41ad-b70c-21fb7216e327 · outbound

This paper cites Ethnologue: Languages of the world, 2025.

The State of Large Language Models for African Languages: Progress and Challenges Ethnologue: Languages of the world, 2025

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:21.369840Z

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Observation 6382c1fd-89f1-4912-abc1-f26cdb4af5a1 · outbound

This paper cites Language-agnostic BERT sentence embedding.

The State of Large Language Models for African Languages: Progress and Challenges Language-agnostic BERT sentence embedding

Reference 16

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Observation 1adfb3d7-6e25-4993-8e7e-8ab058755d73 · outbound

This paper cites Guerreiro, Duarte M.

The State of Large Language Models for African Languages: Progress and Challenges Guerreiro, Duarte M

Reference 17

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Source-reported events for the cited work

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Observation 8c54d4ca-0db1-48a4-acb5-c7226d8de970 · outbound

This paper cites Training Compute-Optimal Large Language Models.

The State of Large Language Models for African Languages: Progress and Challenges Training Compute-Optimal Large Language Models

Reference 18

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Source-reported events for the cited work

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Observation 7d5310d6-1dca-4b94-b880-517890fd6eb8 · outbound

This paper cites Glot500: Scaling multilingual corpora and language models to 500 languages.

The State of Large Language Models for African Languages: Progress and Challenges Glot500: Scaling multilingual corpora and language models to 500 languages

Reference 19

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Observation cf224bba-82b6-41a1-8ed4-868b53209f75 · outbound

This paper cites A fri T e VA : Extending ?small data? pretraining approaches to sequence-to-sequence models.

The State of Large Language Models for African Languages: Progress and Challenges A fri T e VA : Extending ?small data? pretraining approaches to sequence-to-sequence models

Reference 20

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Observation 4acd185a-5fa6-4043-b52d-b158168a80ec · outbound

This paper cites I ndo LEM and I ndo BERT : A benchmark dataset and pre-trained language model for I ndonesian NLP.

The State of Large Language Models for African Languages: Progress and Challenges I ndo LEM and I ndo BERT : A benchmark dataset and pre-trained language model for I ndonesian NLP

Reference 21

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Observation 1607e442-d972-4c85-9855-d7013fa5c9ab · outbound

This paper cites Cross-lingual language model pretraining.

The State of Large Language Models for African Languages: Progress and Challenges Cross-lingual language model pretraining

Reference 22

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Observation 46ec1e55-256e-4a9e-93e0-e6f19d44e645 · outbound

This paper cites BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension.

The State of Large Language Models for African Languages: Progress and Challenges BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 23

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Observation 596bd67d-89e2-4ac1-9648-bf70aa533c77 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

The State of Large Language Models for African Languages: Progress and Challenges RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 24

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Observation c56b29f5-1779-437c-897a-ba36dc60feca · outbound

This paper cites Scaling laws for fact memorization of large language models.

The State of Large Language Models for African Languages: Progress and Challenges Scaling laws for fact memorization of large language models

Reference 25

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Observation a2e314a6-30ea-4a73-ba0d-8feff75fbc06 · outbound

This paper cites F in GPT : Large generative models for a small language.

The State of Large Language Models for African Languages: Progress and Challenges F in GPT : Large generative models for a small language

Reference 26

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Observation de7d1893-e333-43e9-babc-8fc41a9a51dd · outbound

This paper cites A ra T 5: Text-to-text transformers for A rabic language generation.

The State of Large Language Models for African Languages: Progress and Challenges A ra T 5: Text-to-text transformers for A rabic language generation

Reference 27

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Observation 6f4d2d0a-7a97-4d77-a12e-300c63d5ce52 · outbound

This paper cites Small data? no problem! exploring the viability of pretrained multilingual language models for low-resourced african languages.

The State of Large Language Models for African Languages: Progress and Challenges Small data? no problem! exploring the viability of pretrained multilingual language models for low-resourced african languages

Reference 28

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Observation 90c0fd41-2149-4724-b0c9-5235840473b5 · outbound

This paper cites Gpt-4 technical report, 2023.

The State of Large Language Models for African Languages: Progress and Challenges Gpt-4 technical report, 2023

Reference 29

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Observation 03f1b966-88f7-4f75-ad5c-ede8fa14ca70 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

The State of Large Language Models for African Languages: Progress and Challenges Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 30

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The State of Large Language Models for African Languages: Progress and Challenges Bert multilingual model readme, 2019

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:21.280890Z

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Observation 5880c09b-e1eb-4d49-ab35-6a34003be8ae · outbound

This paper cites Multilingual t5: Massively multilingual pre-trained text-to-text transformer, 2021.

The State of Large Language Models for African Languages: Progress and Challenges Multilingual t5: Massively multilingual pre-trained text-to-text transformer, 2021

Reference 32

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Observation ba1d6127-8c37-422e-b29f-b27e20dc8b41 · outbound

This paper cites NLLB-200 : Distilled 600m-parameter model of No Language Left Behind ( NLLB ), 2022.

The State of Large Language Models for African Languages: Progress and Challenges NLLB-200 : Distilled 600m-parameter model of No Language Left Behind ( NLLB ), 2022

Reference 33

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Observation 4f8376fa-4cab-4c36-afa5-49c46958233a · outbound

This paper cites How good is your tokenizer? on the monolingual performance of multilingual language models.

The State of Large Language Models for African Languages: Progress and Challenges How good is your tokenizer? on the monolingual performance of multilingual language models

Reference 34

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This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

The State of Large Language Models for African Languages: Progress and Challenges DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 35

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This paper cites The language barrier: Dissecting safety challenges of LLM s in multilingual contexts.

The State of Large Language Models for African Languages: Progress and Challenges The language barrier: Dissecting safety challenges of LLM s in multilingual contexts

Reference 36

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Observation 23004449-b85d-4a41-9d3f-c47e908c8c05 · outbound

This paper cites Gemini: A family of highly capable multimodal models, December 2023.

The State of Large Language Models for African Languages: Progress and Challenges Gemini: A family of highly capable multimodal models, December 2023

Reference 37

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Observation 20e55edb-7efa-4583-841d-149e9b5181bb · outbound

This paper cites Costa-jussà, James Cross, Onur Çelebi, Maha Elbayad, Kenneth Heafield, Kevin Heffernan, Elahe Kalbassi, Janice Lam, Daniel Licht, Jean Maillard, et al.

The State of Large Language Models for African Languages: Progress and Challenges Costa-jussà, James Cross, Onur Çelebi, Maha Elbayad, Kenneth Heafield, Kevin Heffernan, Elahe Kalbassi, Janice Lam, Daniel Licht, Jean Maillard, et al

Reference 38

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Observation ef751f80-1672-4bcd-a625-b5abee9a1909 · outbound

This paper cites EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation.

The State of Large Language Models for African Languages: Progress and Challenges EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation

Reference 39

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Observation 87f985d4-aa3c-4719-b3c8-61fb6e5c02c3 · outbound

This paper cites E thio LLM : Multilingual large language models for E thiopian languages with task evaluation.

The State of Large Language Models for African Languages: Progress and Challenges E thio LLM : Multilingual large language models for E thiopian languages with task evaluation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:21.187353Z

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Observation 97667762-d008-4c3d-a254-e9977070e972 · outbound

This paper cites E thio MT : Parallel corpus for low-resource E thiopian languages.

The State of Large Language Models for African Languages: Progress and Challenges E thio MT : Parallel corpus for low-resource E thiopian languages

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:31:21.172576Z

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Observation 83dcaf8f-26d2-4c35-bbfe-b1ef1e03b5a5 · outbound

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The State of Large Language Models for African Languages: Progress and Challenges Aya model: An instruction finetuned open-access multilingual language model

Reference 42

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This paper cites A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness.

The State of Large Language Models for African Languages: Progress and Challenges A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness

Reference 43

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This paper cites Chain-of-thought prompting elicits reasoning in large language models.

The State of Large Language Models for African Languages: Progress and Challenges Chain-of-thought prompting elicits reasoning in large language models

Reference 44

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Observation b18aaf85-cd10-4528-bcf8-97b7a9b56839 · outbound

This paper cites BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

The State of Large Language Models for African Languages: Progress and Challenges BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 45

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Observation e4c0cbba-9496-44c1-b415-289b4014c78e · outbound

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The State of Large Language Models for African Languages: Progress and Challenges Unresolved cited work

Reference 46

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Observation cda4dac2-4240-426a-b36d-0b09db8f689b · outbound

This paper cites m T 5: A massively multilingual pre-trained text-to-text transformer.

The State of Large Language Models for African Languages: Progress and Challenges m T 5: A massively multilingual pre-trained text-to-text transformer

Reference 47

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Observation 5d8fe745-4ecd-4917-a8ae-86e683895cdd · outbound

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The State of Large Language Models for African Languages: Progress and Challenges B y T 5: Towards a token-free future with pre-trained byte-to-byte models

Reference 48

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Pith citing papers

Observation 7d8b5202-beec-4f59-9557-28f4fc1c0040 · inbound

AfroScope: A Framework for Studying the Linguistic Landscape of Africa cites this paper.

AfroScope: A Framework for Studying the Linguistic Landscape of Africa The State of Large Language Models for African Languages: Progress and Challenges

Reference 2025

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