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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-06T06:34:29.942622+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 2026-08-06T06:34:29.942622+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:bec31fdfe8367dc49350662fde6876b1f37155b0838524788cb9da5769ee8a8f

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T14:11:11.330888Z digest=sha256:b5cf083983bd87b37f47862cf1cf513b64fd4cbe4d5c5c3c0e6fa9ed8555ef17

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=sha256:46219ecf2f830d703434302caecf9f18e88bf94e04d94a4d41d40e2dca9fc16b

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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source=pdf_text observed=2026-08-06T14:11:11.588449Z digest=sha256:5957794a4039bbce84f2f32aefa3e7b7e13d8906b7a7a27890169251f7d44031

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T14:11:11.728309Z digest=sha256:7f100a320eaee3dcd402b3bbde6419d95fdb89f55c9ffb8b39e21d94416be0e6

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=sha256:32668e7700fddc6850ca63fa8a553707448a7658944e66f3da2b2e100c7b107d

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:d3d6fb90b5c0f20bbe4a4be3dd2ed627810133742e72e6a126bd41ecdd867b03

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T14:11:11.942315Z digest=sha256:4935c1060285986e1dccb96777e57e8dddba5b10e0b603e1a5590d5bc0fcae05

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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source=pdf_text observed=2026-08-06T14:11:12.018398Z digest=sha256:e5b65d9aee8abce9a697dcbb9e0a7f38f77f0dd2221b76bd6229a9b75948a071

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:aeaaa74e63429ca2079c9b05d615677b36d195c76c273d0b3df069ede56cb9bb

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=sha256:9c0e3abf8b7ae8fea240a32d03285dfca838f55d990b8d3be0bf5dd9cbcb5366

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T14:11:12.243495Z digest=sha256:abd5527d6557c227210eb4d6d5909c86833cb807c3cae19f8494b1b3f0a9f640

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T14:11:12.306425Z digest=sha256:0d95f8bef13533d4cf52fe13b6716ac54b7bd797bb309e5b86e8eb19da6e35e4

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:a85d5b1e9247f9e08ee4dbfa0f918bfe1e2ff51d14e8cf5458c192f7927b61e6

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=sha256:5c88868231b58801114d5910f688e25044a89baa8fbb91b381edd4dc69fe2c43

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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source=pdf_text observed=2026-08-06T14:11:12.501822Z digest=sha256:f4e630217ff1a8adc731b078b2e06b22e41dacdb1bba922965d6fbbbc9533c42

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T14:11:12.576237Z digest=sha256:cb60fabe5263e61e188adbbde32a6e232770a592f82ece9e637a1f935870042e

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T14:11:12.639943Z digest=sha256:8997dd41af85a99c2c0e47cf01f571db482ee44d03c33835751281194a242d00

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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source=pdf_text observed=2026-08-06T14:11:12.678100Z digest=sha256:13996de6d5d4684c2500cc357a36a0df918f054088cbec1cbcf993a13b4cf6be

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T14:11:12.716285Z digest=sha256:297457a3abebcbe705e68796e96be642fa549ecad4b6a345600b614c04cbeef0

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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source=pdf_text observed=2026-08-06T14:11:12.780442Z digest=sha256:def245e5593bd1f2e987ac2f22e96474ef236dedd65f21f0d5da09a27f2f7c1b

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 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T14:11:12.853110Z digest=sha256:06cb6774715081584e4518a5ba871ee15425445d07bcbb0464a5ab1991a3cbb9

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:d25963d23e47d82d61eb51110a161765ca67b0de310b95de74f9a3a5d861f2af

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=sha256:86c4439d875e114874391fc0a4c93a25fc376479db2d0c3581ba24bf2c799e71

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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source=pdf_text observed=2026-08-06T14:11:13.066256Z digest=sha256:0f187f9432e5fd1598aaa815d45b508486898e7ec99e0c683a50a158f996c6c7

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:11:13.161086Z digest=sha256:93de1456dd29d33a1fa3518ad1d9a607df7fea172d7dcfe345285e9066bdd028

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:d1440de6ea470233370e2d379afcb122904e88f0078712d330f0edfdea31d3c8

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:a89834bcfab25fc84d63f69f193e8f46365c50b64ec850d30b74518c408b3156

Pith citing papers

No inbound Pith citation observations are available.