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Paper Citation Record · LEDGER

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages

As of 5 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2510.05291.

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

pith.paper-citation-record.v1
2510.05291 v2

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T11:21:59.130531Z

measured 45 of 45 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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Reference resolution

45 of 45 outbound references displayed

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Outbound references

Observation 18db6307-6cbb-42c5-9491-0a63b8f8c3ea · outbound

This paper cites Towards measuring and modeling “culture” in LLMs: A survey.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Towards measuring and modeling “culture” in LLMs: A survey

Reference 1

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Observation 511b9759-897a-4a0f-9ead-71187afff179 · outbound

This paper cites The Indian drink [MASK] is very nice to have in the evening.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages The Indian drink [MASK] is very nice to have in the evening

Reference 3

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Observation 9e6c7c22-b12c-4577-a018-f2d20a070520 · outbound

This paper cites ISBN 979-8-89176- 251-0.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages ISBN 979-8-89176- 251-0

Reference 4

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Observation 5a000da7-b6a6-4886-b2bd-48e9e341fffc · outbound

This paper cites acl-short.75.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages acl-short.75

Reference 5

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source=pdf_text observed=2026-08-04T11:21:54.491285Z digest=sha256:6a765afc4fccd503282a52d0051670d14817f8d2642794e1d5535c47573009b3

Observation 41c9f02a-c45f-4980-9c8c-2e16d5844a46 · outbound

This paper cites Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier

Reference 9

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source=pdf_text observed=2026-08-04T11:21:54.727566Z digest=sha256:1ac85bbe6cc02da69706dce676e758fea66f3f42ec06f5a2f5756a3bba0720c8

Observation 90a698ea-b158-45b2-89a3-f6796fe22c0d · outbound

This paper cites Gender bias in large language models across multiple languages: A case study of ChatGPT.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Gender bias in large language models across multiple languages: A case study of ChatGPT

Reference 10

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source=pdf_text observed=2026-08-04T11:21:54.801763Z digest=sha256:dfd39c08351779ee0f233b8c6827c1a10c923ce6bd4a66abc429babc88373645

Observation b59114fd-3e74-4e6b-a1bc-99c695e0ed80 · outbound

This paper cites Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking

Reference 11

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Observation 2ed28bf0-3893-4eef-9e6f-82b487bc5dda · outbound

This paper cites The Llama 3 Herd of Models.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages The Llama 3 Herd of Models

Reference 12

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source=pdf_text observed=2026-08-04T11:21:54.958728Z digest=sha256:2847bad74e3cecb04ec41aa0fc60bc79006e7171916bfa0acf2012be7794e0ed

Observation 31978471-3741-4244-81f8-07deaa3aa347 · outbound

This paper cites Care: Aligning language models for regional cultural awareness.arXiv preprint arXiv:2504.05154,.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Care: Aligning language models for regional cultural awareness.arXiv preprint arXiv:2504.05154,

Reference 13

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source=pdf_text observed=2026-08-04T11:21:55.062568Z digest=sha256:b2771ec7ecbab7fb99f5b06eb0e616ebb2d180206868af5db4d296f741252c9b

Observation 2c9f2d81-797d-49fb-afb3-0fd641ae5cd7 · outbound

This paper cites Speaking Multiple Languages Affects the Moral Bias of Language Models.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Speaking Multiple Languages Affects the Moral Bias of Language Models

Reference 14

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source=pdf_text observed=2026-08-04T11:21:55.358833Z digest=sha256:390cfeb5b7ef0646567aae165121f9ee8dc200193955ac006f7254254857ad50

Observation 3ea6d102-4e19-4f3d-a7de-d7b6ad729ec1 · outbound

This paper cites TWBias: A benchmark for assessing so- cial bias in traditional chinese large language models through a taiwan cultural lens.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages TWBias: A benchmark for assessing so- cial bias in traditional chinese large language models through a taiwan cultural lens

Reference 15

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Observation f3063778-4f64-47f3-a354-e37cb9365fdd · outbound

This paper cites CBBQ: A Chinese Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages CBBQ: A Chinese Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models

Reference 16

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source=pdf_text observed=2026-08-04T11:21:55.744048Z digest=sha256:be1aa8bb4c9ce82c3b81fb5f2b6972f1307736857abd64ed84486ca976808d3b

Observation 934f4b2f-a8a5-4f0e-86d9-d159e5c448f6 · outbound

This paper cites Gender Bias in Masked Language Models for Multiple Languages.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Gender Bias in Masked Language Models for Multiple Languages

Reference 17

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source=pdf_text observed=2026-08-04T11:21:55.882487Z digest=sha256:76d79e93d46b5c3a848c6bb9a23aaf034148ca8282e75be20d3b26227b73e45c

Observation bd19f1ef-516e-4072-b040-df348de27172 · outbound

This paper cites DLAMA: A Framework for Curating Culturally Diverse Facts for Probing the Knowledge of Pretrained Language Models.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages DLAMA: A Framework for Curating Culturally Diverse Facts for Probing the Knowledge of Pretrained Language Models

Reference 18

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Observation dcb47e15-903c-4418-9f64-2f1fc147d8d6 · outbound

This paper cites McBE: A Multi-task Chinese Bias Evaluation Benchmark for Large Language Models.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages McBE: A Multi-task Chinese Bias Evaluation Benchmark for Large Language Models

Reference 19

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source=pdf_text observed=2026-08-04T11:21:56.069608Z digest=sha256:2d0980c4cd099882754c0168db9bc8db671c23f3c0762deeecb9183ccb240033

Observation 76e1b81a-d956-46dc-b388-d72fdcc7ff51 · outbound

This paper cites What are foundation models cooking in the post-soviet world?arXiv preprint arXiv:2502.18583,.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages What are foundation models cooking in the post-soviet world?arXiv preprint arXiv:2502.18583,

Reference 20

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source=pdf_text observed=2026-08-04T11:21:56.213528Z digest=sha256:c890e4035e31347d3a022910f7eb9317deb0b8a27ff3d9faa6d0e22a9be3c9d2

Observation b5876175-5402-4f3e-b261-c77d0992a8f8 · outbound

This paper cites Comparing Biases and the Impact of Multilingual Training across Multiple Languages.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Comparing Biases and the Impact of Multilingual Training across Multiple Languages

Reference 21

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Observation 7073e39e-411f-4e20-b387-10edefffb19b · outbound

This paper cites Attributing Culture-Conditioned Generations to Pretraining Corpora.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Attributing Culture-Conditioned Generations to Pretraining Corpora

Reference 22

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Observation ede2c501-f32e-4ace-adc8-91d4d864ef96 · outbound

This paper cites Probing politico-economic bias in multilingual large lan- guage models: A cultural analysis of low-resource pakistani languages.arXiv preprint arXiv:2506.00068,.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Probing politico-economic bias in multilingual large lan- guage models: A cultural analysis of low-resource pakistani languages.arXiv preprint arXiv:2506.00068,

Reference 23

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Observation f8f39240-8114-4dd5-b127-38602acecbcb · outbound

This paper cites On the origin of cultural biases in language models: From pre-training data to linguistic phenomena.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages On the origin of cultural biases in language models: From pre-training data to linguistic phenomena

Reference 24

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Observation eaeca37a-5a23-46c4-81b1-5b06b99ea956 · outbound

This paper cites ISBN 979-8-89176-189-6.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages ISBN 979-8-89176-189-6

Reference 25

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source=pdf_text observed=2026-08-04T11:21:56.497276Z digest=sha256:a009d2e92353f0b89da524c64c168e2242407a31533663b41b1523f5c149d9d4

Observation 6601a751-5d68-465b-95c2-ec050913c1fc · outbound

This paper cites "You Gotta be a Doctor, Lin": An Investigation of Name-Based Bias of Large Language Models in Employment Recommendations.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages "You Gotta be a Doctor, Lin": An Investigation of Name-Based Bias of Large Language Models in Employment Recommendations

Reference 26

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source=pdf_text observed=2026-08-04T11:21:56.592115Z digest=sha256:4ebfe33dff9fb35fedf45e140415866f3922e38ea9c870234748209af36772f8

Observation 29e732b2-1e0d-438e-884f-379a3081aaa4 · outbound

This paper cites FORK: A bite-sized test set for probing culinary cultural biases in com- monsense reasoning models.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages FORK: A bite-sized test set for probing culinary cultural biases in com- monsense reasoning models

Reference 27

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Observation d4684197-a5b6-4e84-9bc3-57b9be45ed1e · outbound

This paper cites BBQ: A Hand-Built Bias Benchmark for Question Answering.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages BBQ: A Hand-Built Bias Benchmark for Question Answering

Reference 28

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source=pdf_text observed=2026-08-04T11:21:56.896943Z digest=sha256:c561ee013361b14c29f28aefd57e86ab22d772e78a2d70b7485c3ef3b4ae6253

Observation 418d4279-313d-4849-ac0c-6c1b4c69c232 · outbound

This paper cites Purdah and Patriarchy: Evaluating and Mitigating South Asian Biases in Open-Ended Multilingual LLM Generations.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Purdah and Patriarchy: Evaluating and Mitigating South Asian Biases in Open-Ended Multilingual LLM Generations

Reference 31

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source=pdf_text observed=2026-08-04T11:21:57.321318Z digest=sha256:af0d8e290fd0cdf37433b652be99b6632b766c0210ef6c52d5ca0e2a343b8e03

Observation e484148c-77b0-4559-8101-102a62eae0cb · outbound

This paper cites INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge

Reference 32

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source=pdf_text observed=2026-08-04T11:21:57.468081Z digest=sha256:bb675149ab71297a60996d8dde773238d2321488466a2767611ff41c363ff4e5

Observation c044eadd-ccc8-4f7d-bbd6-d9eca4e12ad6 · outbound

This paper cites CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

Reference 33

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source=pdf_text observed=2026-08-04T11:21:57.622339Z digest=sha256:02dcd20c2a3dba55a9505736a16b6a587f92749b8565a1d35339555a56209568

Observation 74c9592a-b8f5-4c2c-88ce-2d1102a19308 · outbound

This paper cites IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context

Reference 34

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Observation de0732b7-52c5-48bc-8c8d-055a372e3169 · outbound

This paper cites Gemma 3 Technical Report.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Gemma 3 Technical Report

Reference 35

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source=pdf_text observed=2026-08-04T11:21:57.852679Z digest=sha256:fa7bae5b0335aea348a0080fc301a7dd78e0d62fd35ea0494965ab9867436239

Observation 3bbd82d0-7ffa-41ae-98eb-92a8ffbe9f68 · outbound

This paper cites On Evaluating and Mitigating Gender Biases in Multilingual Settings.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages On Evaluating and Mitigating Gender Biases in Multilingual Settings

Reference 36

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Observation 2609908e-1393-4202-8aed-f5711fc22fc9 · outbound

This paper cites kelly is a warm per- son, joseph is a role model.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages kelly is a warm per- son, joseph is a role model

Reference 37

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Observation 25a6e566-ce5c-46ca-b8aa-dd1a1d4b48d4 · outbound

This paper cites Multilingual prompting for improving llm generation diversity.arXiv preprint arXiv:2505.15229,.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Multilingual prompting for improving llm generation diversity.arXiv preprint arXiv:2505.15229,

Reference 38

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source=pdf_text observed=2026-08-04T11:21:58.223178Z digest=sha256:f684f8fe6687416cd141482c21cc8983891ccf9f0417d92b20c092d5388cb39a

Observation 6d22b049-492e-43d3-9162-f185eaf181ac · outbound

This paper cites WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines

Reference 39

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source=pdf_text observed=2026-08-04T11:21:58.320139Z digest=sha256:526115f4ecdd483153561b29f95f32f7e427923aa7439ccccdcd8bd1d38a948d

Observation 8ab933fc-acec-4fe6-9dc3-f0b326f3ba67 · outbound

This paper cites Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models

Reference 40

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Observation 2d8f5a70-0d6e-403f-a814-055aa5015f6f · outbound

This paper cites mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer

Reference 41

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Observation b6f300f0-b168-4b9e-b620-594b5fbfa148 · outbound

This paper cites Qwen2.5 Technical Report.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Qwen2.5 Technical Report

Reference 42

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Observation 6930fb88-ea83-4141-a8d2-8f07fcb0ee24 · outbound

This paper cites CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages CHBias: Bias Evaluation and Mitigation of Chinese Conversational Language Models

Reference 43

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source=pdf_text observed=2026-08-04T11:21:58.895581Z digest=sha256:6b105c6b6f9b0bb0b228e8dd42258f33fa77a10f33dfeee83b72495a02be5a7f

Observation bf0c37ee-5235-4a0b-8d1a-d8fed748a154 · outbound

This paper cites Does Mapo Tofu Contain Coffee? Probing LLMs for Food-related Cultural Knowledge.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Does Mapo Tofu Contain Coffee? Probing LLMs for Food-related Cultural Knowledge

Reference 44

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source=pdf_text observed=2026-08-04T11:21:59.018142Z digest=sha256:737082db1426535601f084380348f04ef554681247520a997fd35ff0364535aa

Observation caf64583-f016-45d1-b9f1-c1bd0b157b41 · outbound

This paper cites NormAd: A Framework for Measuring the Cultural Adaptability of Large Language Models.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages NormAd: A Framework for Measuring the Cultural Adaptability of Large Language Models

Reference 2017

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source=pdf_text observed=2026-08-04T11:21:57.130065Z digest=sha256:be80329227e1bde9ca5ea25581f3a4801d03b3ffd2675f8acfa9c40a0543ef7a

Observation 64f8ec58-24ad-4bde-8ddf-30a645a53cd6 · outbound

This paper cites Multilingual Holistic Bias: Extending Descriptors and Patterns to Unveil Demographic Biases in Languages at Scale.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Multilingual Holistic Bias: Extending Descriptors and Patterns to Unveil Demographic Biases in Languages at Scale

Reference 2018

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source=pdf_text observed=2026-08-04T11:21:54.622358Z digest=sha256:91e032f0820875b112f94b9951792ff60d54d2188b4ea9a0629c76a1783818a7

Observation 5b54187b-e1a6-4b0c-8a40-d9afc76a5abe · outbound

This paper cites Presumed Cultural Identity: How Names Shape LLM Responses.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Presumed Cultural Identity: How Names Shape LLM Responses

Reference 2021

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no resolver link, observed 2026-08-04T11:21:56.996228Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T11:21:56.996228Z digest=sha256:1d8830f5c1419f540569ad856a38b74a473c120c1c972f38a3c256b608e9238e

Observation 70060888-ff71-46dc-8996-b3fb9096ee50 · outbound

This paper cites CulturalTeaming: AI-Assisted Interactive Red-Teaming for Challenging LLMs' (Lack of) Multicultural Knowledge.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages CulturalTeaming: AI-Assisted Interactive Red-Teaming for Challenging LLMs' (Lack of) Multicultural Knowledge

Reference 2022

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source=pdf_text observed=2026-08-04T11:21:54.566588Z digest=sha256:cf36d780ba5616c3fe5a881f549d155a19e63476c15d260442e8543375e62d5e

Observation 9debe51b-5d08-4ad7-a3cc-d1af571fcdf1 · outbound

This paper cites they are uncultured.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages they are uncultured

Reference 2023

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T11:21:54.679667Z digest=sha256:8a42b40316a1a47ec886a6883285570a2593d26f9f4e15cfdf43215a99fd9cfb

Observation 72956fa8-e4e0-4b12-be07-02a5dace9114 · outbound

This paper cites Palm: A Culturally Inclusive and Linguistically Diverse Dataset for Arabic LLMs.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Palm: A Culturally Inclusive and Linguistically Diverse Dataset for Arabic LLMs

Reference 2024

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source=pdf_text observed=2026-08-04T11:21:54.213729Z digest=sha256:e15af734456fffa6dc919c651b990a80f1f41a92a5f361dd1fe24ae114b5d3f4

Observation 43bf2bf8-5369-4ab4-be1f-5bc0c12f848b · outbound

This paper cites Do Large Language Models Discriminate in Hiring Decisions on the Basis of Race, Ethnicity, and Gender?.

Camellia: Benchmarking Cultural Biases in LLMs for Asian Languages Do Large Language Models Discriminate in Hiring Decisions on the Basis of Race, Ethnicity, and Gender?

Reference 2025

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source=pdf_text observed=2026-08-04T11:21:54.299309Z digest=sha256:c4c5c3dae76b958b893f2c497af72780a46464e99185f8b8ad8eb2f54c38f2d9

Pith citing papers

No inbound Pith citation observations are available.