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Paper Citation Record · LEDGER

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks

As of 17 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2507.19699.

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

pith.paper-citation-record.v1
2507.19699 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:11:13.303967Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

30 of 30 outbound references displayed

  • verified exact1
  • verified fuzzy4
  • unresolved19
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 61d5d5f5-0995-43c2-a188-1d85d7ceea5e · outbound

This paper cites In: Proceedings of ArabicNLP 2023.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks In: Proceedings of ArabicNLP 2023

Reference 1

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raw_fallback, observed 2026-08-06T14:11:16.371459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation eec9bd77-5944-4aa2-95bd-647647df829c · outbound

This paper cites AraGPT2: Pre-Trained Transformer for Arabic Language Generation.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks AraGPT2: Pre-Trained Transformer for Arabic Language Generation

Reference 2

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source=pdf_text observed=2026-08-06T14:11:11.188883Z digest=sha256:dbdc25cc0576620fd08d912e3e46bb4b603ed478f338d1365ff8a6317e8cbf4f

Observation af598cc7-5762-43e7-b770-7beb39ca2dd9 · outbound

This paper cites 1–8 (2024).

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks 1–8 (2024)

Reference 3

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:11.330888Z digest=sha256:7274a3c02d90724f061aa4d3bc833c13af225fd498d9353bee06ffc56037e792

Observation 0e962d46-608a-44a2-a2a4-0c430667e621 · outbound

This paper cites ALLaM: Large Language Models for Arabic and English.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks ALLaM: Large Language Models for Arabic and English

Reference 4

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source=pdf_text observed=2026-08-06T14:11:11.460009Z digest=sha256:456e4b6f5a335d12feebeb7b88293194387fee4951c33385ccac46e4fc801511

Observation 292c3ea1-7a35-4238-beb9-f5066bcc2c11 · outbound

This paper cites Analyzing Multilingual Competency of LLMs in Multi-Turn Instruction Following: A Case Study of Arabic.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Analyzing Multilingual Competency of LLMs in Multi-Turn Instruction Following: A Case Study of Arabic

Reference 5

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local_arxiv, observed 2026-08-06T14:11:14.910753Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:11.588449Z digest=sha256:df7da0f959caa9892a54b81502869952466005d5934bfc3ef3870dab73a09cb7

Observation ccad495e-4262-4535-8da9-0ca1312791fc · outbound

This paper cites A Reality check of the benefits of LLM in business.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks A Reality check of the benefits of LLM in business

Reference 6

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local_arxiv, observed 2026-08-06T14:11:14.775153Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:11.728309Z digest=sha256:b273ddc4b6e1f90d8503a0186d17b8cb7a999da7d01ce09aaac19b8f5ecedd01

Observation 23c660d7-4f23-4cc0-8d12-43ab46acf99c · outbound

This paper cites arXiv preprint arXiv:2503.11733 (2025).

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks arXiv preprint arXiv:2503.11733 (2025)

Reference 7

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source=pdf_text observed=2026-08-06T14:11:11.850969Z digest=sha256:c8b6018bca04786337a7797dfba4af95618d56d02daa5372a30baf5253be7b80

Observation 797999e5-6d31-44bf-a2f1-7dd5816a83bb · outbound

This paper cites Better to Ask in English: Evaluation of Large Language Models on English, Low-resource and Cross-Lingual Settings.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Better to Ask in English: Evaluation of Large Language Models on English, Low-resource and Cross-Lingual Settings

Reference 8

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source=pdf_text observed=2026-08-06T14:11:11.887553Z digest=sha256:4c50c0e80d4cbd634f11385d1ede36dc31bd64ed1c46a2000fefc05a4cafccd5

Observation 5512ef74-2b60-42cb-90f3-9ef325b31ff7 · outbound

This paper cites IEEE Transactions on Artificial Intelligence 5(12), 5873–5893 (2024).

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks IEEE Transactions on Artificial Intelligence 5(12), 5873–5893 (2024)

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:11.942315Z digest=sha256:c7f6cfcfcd426a12cf5ba10979a3087ebe1d9344cc539a60cf2ea3576dfd62b8

Observation a800f622-8927-44e0-9e68-ee0ac5b8befe · outbound

This paper cites Do Large Language Models Speak All Languages Equally? A Comparative Study in Low-Resource Settings.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Do Large Language Models Speak All Languages Equally? A Comparative Study in Low-Resource Settings

Reference 10

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Observation 81e281db-80e0-432d-9d0b-d556c897dcce · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Measuring Massive Multitask Language Understanding

Reference 11

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Observation 55332fcd-d64d-48d0-acc8-99eca9cb1647 · outbound

This paper cites arXiv preprint arXiv:2408.07983 (2024).

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks arXiv preprint arXiv:2408.07983 (2024)

Reference 12

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source=pdf_text observed=2026-08-06T14:11:12.119121Z digest=sha256:e07367a432897cdcf6c4ac77e2e1cdc130081485f38872899a5f5cecec409b3b

Observation d5e523c9-6f9f-4067-b009-19aa86acb841 · outbound

This paper cites AceGPT, Localizing Large Language Models in Arabic.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks AceGPT, Localizing Large Language Models in Arabic

Reference 13

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source=pdf_text observed=2026-08-06T14:11:12.182812Z digest=sha256:eec9906921a566912d083da4dcba43d1f0dc325e46f196b74314ce3a7e3fbf39

Observation 468e2a2c-25d7-493e-8f8c-be160830cce3 · outbound

This paper cites https://huggingface.co/datasets/Indic-Benchmark/kannada-arc-c-2.5k (2023).

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks https://huggingface.co/datasets/Indic-Benchmark/kannada-arc-c-2.5k (2023)

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:12.243495Z digest=sha256:8eee86052627f1ecc7a08175dcbc648d99333759f87d90535829b553c1ca4e2f

Observation 311d39e2-466b-47ae-ac64-3f46161a0868 · outbound

This paper cites ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic

Reference 15

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local_arxiv, observed 2026-08-06T14:11:13.921117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:12.306425Z digest=sha256:70dea16dd927232eb93cfcba3844737e72b1fb4aee12115d12f95cfa3cbde781

Observation f6d59593-ba64-4028-8ae6-c3647b1c6d91 · outbound

This paper cites THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models

Reference 16

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source=pdf_text observed=2026-08-06T14:11:12.382543Z digest=sha256:f668f391c84e71ffb96679417f3b35f153d4226cc1ed61e5b7621e81a88880c3

Observation 3d618714-9f22-4c1d-b92a-5069dfa5476e · outbound

This paper cites Few-shot Learning with Multilingual Language Models.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Few-shot Learning with Multilingual Language Models

Reference 17

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source=pdf_text observed=2026-08-06T14:11:12.446620Z digest=sha256:f85010d9b8c3db690768ab501f50831e6feb2afc8177c6aa2d4cdd24da3f302b

Observation 25981187-d34c-461a-8f1b-475ba56295fd · outbound

This paper cites In: Proceedings of In- terspeech 2024.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks In: Proceedings of In- terspeech 2024

Reference 18

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Observation 0bee8bde-eb89-4068-9c18-3b578db8e8ca · outbound

This paper cites Suvach -- Generated Hindi QA benchmark.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Suvach -- Generated Hindi QA benchmark

Reference 19

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local_arxiv, observed 2026-08-06T14:11:13.720255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:12.576237Z digest=sha256:381c8361d8a8629db304ed4408abef27d8395444632ac33784aa592c3379bf46

Observation 38d19f3c-8372-466c-a3a9-af3fb7fb0acc · outbound

This paper cites In: Informatics.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks In: Informatics

Reference 20

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raw_fallback, observed 2026-08-06T14:11:15.874439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:12.639943Z digest=sha256:f36433350602f9c15b3de0c864777249cdda05b4ba2a52b7ef63dd44d3a2191f

Observation 9598c24e-896f-4653-ae02-dc8c970761a1 · outbound

This paper cites Spanish and LLM Benchmarks: is MMLU Lost in Translation?.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Spanish and LLM Benchmarks: is MMLU Lost in Translation?

Reference 21

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Observation 7449f616-9637-4081-a420-f16f5103766e · outbound

This paper cites IEEE Ac- cess 11, 132516–132531 (2023).

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks IEEE Ac- cess 11, 132516–132531 (2023)

Reference 22

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:12.716285Z digest=sha256:d09953951894f2a3b51bc421d769033e668d2b573056052b128b9d599c105352

Observation cb42084b-0fdc-4d30-b4b3-4ffc0432f123 · outbound

This paper cites Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:11:12.780442Z digest=sha256:f6e2d5ba20584ce073e008dab5f08e4e5a100f204b4e4fa69ddac1ac11f7d783

Observation 0f972bf7-a709-4ab9-ab6b-f28eb054b109 · outbound

This paper cites an unresolved cited work.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Unresolved cited work

Reference 24

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T14:11:12.853110Z digest=sha256:6b90b7d06de46b19b8145a233dae85e2d07289e167726794195fbf1beb453283

Observation 2bda1752-992f-4d3f-b7d6-9b815a55fe1b · outbound

This paper cites IndicGenBench: A Multilingual Benchmark to Evaluate Generation Capabilities of LLMs on Indic Languages.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks IndicGenBench: A Multilingual Benchmark to Evaluate Generation Capabilities of LLMs on Indic Languages

Reference 25

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:11:12.922792Z digest=sha256:2310bc5512997889980b80e702c6ef6d5c2cbc672f333e3f5e3c746a87091340

Observation 563518c4-1ddd-463c-b440-57685e23b800 · outbound

This paper cites MMLU-Pro+: Evaluating Higher-Order Reasoning and Shortcut Learning in LLMs.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks MMLU-Pro+: Evaluating Higher-Order Reasoning and Shortcut Learning in LLMs

Reference 26

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source=pdf_text observed=2026-08-06T14:11:13.013412Z digest=sha256:45a9c8d343ee5baca26e9ba5406a627f1eac493250e4bc4f918a1814c0d1b609

Observation b9efb9bd-4daf-4e55-b9af-110a4d0ffefd · outbound

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

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 27

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:11:13.066256Z digest=sha256:a81db02d7674d6bdf8c86d15c3dfd58f42a5f18caf7e0613435af4472bde284a

Observation 2629489e-4475-4d8e-a6de-385e4ec79920 · outbound

This paper cites Structured Pruning of Large Language Models.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks Structured Pruning of Large Language Models

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:11:13.161086Z digest=sha256:535755cdb2a62f4e385666e1044cafc9a0feb5a46d20bd9497335578e7a1477e

Observation 35d4dd75-f828-4c8c-b128-28f6721cfdbb · outbound

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

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 29

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source=pdf_text observed=2026-08-06T14:11:13.217557Z digest=sha256:a0b6951202702e4b88aefc2df1ab80a1a130e9bafb630975093bd175b5c2e0e1

Observation d49f8fb0-a2f7-488c-890d-ab937df70595 · outbound

This paper cites ZeroQuant-V2: Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation.

Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks ZeroQuant-V2: Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation

Reference 30

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source=pdf_text observed=2026-08-06T14:11:13.303967Z digest=sha256:cf2edbc0867bcbbea905999c4bc0d23bac58240e59c9de70ddb56a399bd9dc75

Pith citing papers

No inbound Pith citation observations are available.