Paper Citation Record · LEDGER

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages

As of 18 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 5 inbound Pith citation observations for arXiv:2506.19468.

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

pith.paper-citation-record.v1
2506.19468 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:36:35.996643Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:17:10.649943Z

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

40 of 40 outbound references displayed

verified exact0
verified fuzzy31
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

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

Outbound references

Observation 98b03044-3a20-4beb-b15a-d62e21f70207 · outbound

This paper cites https://www.anthropic.com/news/claude-3-7- sonnet.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages https://www.anthropic.com/news/claude-3-7- sonnet

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.590000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1d06bff1-adb1-4c2a-b536-8652fb2e3d64 · outbound

This paper cites https://openai.com/index/hello-gpt-4o/.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages https://openai.com/index/hello-gpt-4o/

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.575647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e170ba35-2370-4d50-a6e5-7ee71e86fa26 · outbound

This paper cites https://docs.anthropic.com/en/docs/build-with-claude/multilingual- support.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages https://docs.anthropic.com/en/docs/build-with-claude/multilingual- support

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.561102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 43d641cb-caf4-4ffe-a21d-ee96087d40b8 · outbound

This paper cites https://qwenlm.github.io/blog/qwen3/.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages https://qwenlm.github.io/blog/qwen3/

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.548739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f2f3377b-0996-43bf-9a82-71b2c8a32d5b · outbound

This paper cites https://www.cerebras.ai/blog/slimpajama-a-627b-token-cleaned-and-deduplicated-version-of- redpajama.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages https://www.cerebras.ai/blog/slimpajama-a-627b-token-cleaned-and-deduplicated-version-of- redpajama

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.537022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2b33e47f-0555-4ddd-b267-a19c28153346 · outbound

This paper cites an unresolved cited work.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:36:36.524255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fa721713-73e3-40e9-8e7f-58e2af6ec58a · outbound

This paper cites When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.508957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ec99d56b-849a-4789-8fa6-08cc4a8293a5 · outbound

This paper cites Bowman, Gabor Angeli, Christopher Potts, and Christopher D.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Bowman, Gabor Angeli, Christopher Potts, and Christopher D

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T18:36:35.836435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bd3a764-b1b7-4488-bc5e-ca2cec99fe8d · outbound

This paper cites Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models, March 2025.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models, March 2025

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.482994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b85ca9f9-e540-43a0-8c2d-7041d9e25d95 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge, March 2018.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge, March 2018

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.469955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a29e9fc7-b056-4f24-b63f-28f04e968567 · outbound

This paper cites Emerging Cross-lingual Structure in Pretrained Language Models.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Emerging Cross-lingual Structure in Pretrained Language Models

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.456891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f04a8942-0535-47b0-aa16-f701872a2cd8 · outbound

This paper cites Tran, Mike Zhang, Shiqi Chen, Tianyu Pang, Chao Du, Xinyi Wan, Wei Lu, and Min Lin.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Tran, Mike Zhang, Shiqi Chen, Tianyu Pang, Chao Du, Xinyi Wan, Wei Lu, and Min Lin

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.442754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ab1e1922-a584-4e3d-bd47-2d85e3875240 · outbound

This paper cites Measuring Massive Multitask Language Understanding, January 2021.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Measuring Massive Multitask Language Understanding, January 2021

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T18:36:35.861228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e9b682f-6662-4a3a-88f3-bc2b4059c93e · outbound

This paper cites BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models, February 2025.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models, February 2025

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.419675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 246c5349-1ce6-4dd4-874f-5a5cbe828057 · outbound

This paper cites Evaluating Code- Switching Translation with Large Language Models.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Evaluating Code- Switching Translation with Large Language Models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.404649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fe10d072-5651-429b-9f32-826fae534430 · outbound

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

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.389923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 99bf655d-ca07-4eac-9bd6-792c4bd608be · outbound

This paper cites Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.377679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 23f05cb1-4611-48e0-aab3-35eaf884a8f7 · outbound

This paper cites Cross-lingual Language Model Pretraining, January 2019.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Cross-lingual Language Model Pretraining, January 2019

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.365539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 25ef6dd0-ac2e-42af-8422-ef5f55bfed11 · outbound

This paper cites The Winograd Schema Challenge.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages The Winograd Schema Challenge

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.352897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c65a92f0-4b1e-4118-83e8-6240f5cc6671 · outbound

This paper cites CMMLU: Measuring massive multitask language understanding in Chinese, January 2024.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages CMMLU: Measuring massive multitask language understanding in Chinese, January 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.339722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 874ebfe6-2074-419e-af6b-165b3c29fbca · outbound

This paper cites TruthfulQA: Measuring How Models Mimic Human Falsehoods, May 2022.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages TruthfulQA: Measuring How Models Mimic Human Falsehoods, May 2022

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.327265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 548ab402-ab86-40fe-b10d-3515435425f6 · outbound

This paper cites Few-shot Learning with Multilingual Language Models, November 2022.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Few-shot Learning with Multilingual Language Models, November 2022

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.309882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6c13d83f-24ab-4403-b131-a2a595cd01d1 · outbound

This paper cites A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories, April 2016.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories, April 2016

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.294228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation de2a2721-bf5d-42af-8d45-bcf48bca2370 · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale, October 2024.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale, October 2024

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.282353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 14ab9f1e-bf65-4baf-88ce-68e172d531e5 · outbound

This paper cites Cross-Lingual Consistency of Factual Knowledge in Multilingual Language Models.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Cross-Lingual Consistency of Factual Knowledge in Multilingual Language Models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.271759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 741cad5f-2805-429d-bf59-a6dbd667b067 · outbound

This paper cites Qwen2.5 Technical Report, January 2025.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Qwen2.5 Technical Report, January 2025

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.259326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0cfd18b6-c0a0-4d3b-8a3e-e94a2ce4cd38 · outbound

This paper cites Farinha, and Alon Lavie.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Farinha, and Alon Lavie

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.249062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 069a478c-ba85-46ba-8347-31de6d7836c3 · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T18:36:35.942564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14f09d0d-5100-400d-9409-b8029b4a278b · outbound

This paper cites an unresolved cited work.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:36:36.238669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a20afbec-4b23-4406-a544-717165232b95 · outbound

This paper cites WinoGrande: An Adversarial Winograd Schema Challenge at Scale.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T18:36:35.953037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 837d2353-93f2-4ac1-b566-a7bcce497b62 · outbound

This paper cites an unresolved cited work.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:36:36.226925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3f149561-8e70-44f8-b7e7-7377b1b9afe6 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models, June 2024.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Gemini: A Family of Highly Capable Multimodal Models, June 2024

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.213558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ed20dbda-5be2-435e-a163-eb61afd3a5d1 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size, July 2024.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Gemma 2: Improving Open Language Models at a Practical Size, July 2024

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.197316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ac3a7651-b3d9-4f04-92a1-ff7ae8ee86f8 · outbound

This paper cites Gemma 3 Technical Report, March 2025.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Gemma 3 Technical Report, March 2025

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.182932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6a2718dd-310a-4da3-9463-c30a86374681 · outbound

This paper cites MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark, November 2024.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark, November 2024

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.167618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 01178922-80db-4fee-a5f3-525d8e439acf · outbound

This paper cites A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.153180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f531ad6d-2fd4-4cfd-9853-d90bb11031b2 · outbound

This paper cites MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation, March 2025.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation, March 2025

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.140870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a86a4da5-b507-4506-8c1b-6af4e12c5808 · outbound

This paper cites GeoM- LAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages GeoM- LAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:36:36.124851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e89d369c-9f7d-466d-8b69-4a16717cde6b · outbound

This paper cites an unresolved cited work.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:36:36.105733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d708062e-4b90-4a7e-a6c4-3de2a5f2c57e · outbound

This paper cites imitative falsehoods,.

MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages imitative falsehoods,

Reference 40

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T18:36:36.083545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation d7d670b6-74af-4249-82d0-ad4de16c1c5c · inbound

Cross-Lingual Sentiment Misalignment: Auditing Multilingual Language Models for Inversion Risk, Dialectal Representation, and Affective Stability cites this paper.

Cross-Lingual Sentiment Misalignment: Auditing Multilingual Language Models for Inversion Risk, Dialectal Representation, and Affective Stability MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-15T21:00:17.818057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 730fd3d8-a5e0-4074-bf2d-508a7376e0bb · inbound

Evaluating Cross-lingual Knowledge Consistency in Code-Mixed vis-a-vis Indian Languages using IndicKLAR cites this paper.

Evaluating Cross-lingual Knowledge Consistency in Code-Mixed vis-a-vis Indian Languages using IndicKLAR MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T08:13:15.958889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9c82c7c9-5200-4e50-86b9-ee767e5aaa4f · inbound

Creating Multilingual Mental Health Dialogue Datasets: Limits of Persona-Based Localization via Nationality and Language cites this paper.

Creating Multilingual Mental Health Dialogue Datasets: Limits of Persona-Based Localization via Nationality and Language MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T20:29:57.635151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7e5a3f42-0bc6-4992-9fde-7ea61cbf2cbc · inbound

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

MultiHashFormer: Hash-based Generative Language Models MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-06-29T04:23:05.535623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9720bdf5-582d-4673-9979-f8b6660a096c · inbound

Language Equality has a Price: A Systematic Investigation of Multi-turn LLM Performance for EU-24+ cites this paper.

Language Equality has a Price: A Systematic Investigation of Multi-turn LLM Performance for EU-24+ MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T00:17:10.649943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.