{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:18:00Z","timestamp":1774628280769,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":83,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6,23]]},"DOI":"10.1145\/3715275.3732019","type":"proceedings-article","created":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T17:01:18Z","timestamp":1750698078000},"page":"246-282","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["The World Wide recipe: A community-centred framework for fine-grained data collection and regional bias operationalisation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1088-6122","authenticated-orcid":false,"given":"Jabez","family":"Magomere","sequence":"first","affiliation":[{"name":"University of Oxford, Oxford, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1391-4886","authenticated-orcid":false,"given":"Shu","family":"Ishida","sequence":"additional","affiliation":[{"name":"Autodesk, London, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0639-9668","authenticated-orcid":false,"given":"Tejumade","family":"Afonja","sequence":"additional","affiliation":[{"name":"CISPA Helmholtz Center for Information Security, Saarbr\u00fccken, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7111-7677","authenticated-orcid":false,"given":"Aya","family":"Salama","sequence":"additional","affiliation":[{"name":"Microsoft, Cairo, Egypt"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3468-8221","authenticated-orcid":false,"given":"Daniel","family":"Kochin","sequence":"additional","affiliation":[{"name":"University of Oxford, Oxford, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2092-1013","authenticated-orcid":false,"given":"Yuehgoh","family":"Foutse","sequence":"additional","affiliation":[{"name":"KmerAI, Toulon, France"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7413-5545","authenticated-orcid":false,"given":"Imane","family":"Hamzaoui","sequence":"additional","affiliation":[{"name":"Ecole nationale Sup\u00e9rieure d'Informatique Algiers, Algiers, Algeria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8650-671X","authenticated-orcid":false,"given":"Raesetje","family":"Sefala","sequence":"additional","affiliation":[{"name":"McGill University, Montreal, Canada and Distributed AI Research Institute, Montreal, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0953-1769","authenticated-orcid":false,"given":"Aisha","family":"Alaagib","sequence":"additional","affiliation":[{"name":"Independent researcher, Riyadh, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5604-055X","authenticated-orcid":false,"given":"Samantha","family":"Dalal","sequence":"additional","affiliation":[{"name":"University of Colorado Boulder, Boulder, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2700-6106","authenticated-orcid":false,"given":"Beatrice","family":"Marchegiani","sequence":"additional","affiliation":[{"name":"University of Oxford, Oxford, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8271-2575","authenticated-orcid":false,"given":"Elizaveta","family":"Semenova","sequence":"additional","affiliation":[{"name":"Imperial College London, London, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5003-3538","authenticated-orcid":false,"given":"Lauren","family":"Crais","sequence":"additional","affiliation":[{"name":"Faculty of Law, University of Oxford, Oxford, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1520-4220","authenticated-orcid":false,"given":"Siobhan Mackenzie","family":"Hall","sequence":"additional","affiliation":[{"name":"University of Oxford, Oxford, United Kingdom"}]}],"member":"320","published-online":{"date-parts":[[2025,6,23]]},"reference":[{"key":"e_1_3_3_2_2_2","doi-asserted-by":"crossref","unstructured":"David\u00a0Ifeoluwa Adelani Jade Abbott Graham Neubig Daniel D\u2019souza Julia Kreutzer Constantine Lignos Chester Palen-Michel Happy Buzaaba Shruti Rijhwani Sebastian Ruder et\u00a0al. 2021. MasakhaNER: Named entity recognition for African languages. Transactions of the Association for Computational Linguistics 9 (2021) 1116\u20131131.","DOI":"10.1162\/tacl_a_00416"},{"key":"e_1_3_3_2_3_2","unstructured":"Meta AI. 2024. Introducing Meta Llama 3: The most capable openly available LLM to date. https:\/\/ai.meta.com\/blog\/meta-llama-3\/."},{"key":"e_1_3_3_2_4_2","doi-asserted-by":"publisher","unstructured":"Grace Ataguba Rock Ezekiel James Daniel Emeka Ogbuju and Rita Orji. 2024. African foods for deep learning-based food recognition systems dataset. Data in Brief 53 (2024) 110092. https:\/\/doi.org\/10.1016\/j.dib.2024.110092","DOI":"10.1016\/j.dib.2024.110092"},{"key":"e_1_3_3_2_5_2","unstructured":"Hugo Berg Siobhan\u00a0Mackenzie Hall Yash Bhalgat Wonsuk Yang Hannah\u00a0Rose Kirk Aleksandar Shtedritski and Max Bain. 2022. A prompt array keeps the bias away: Debiasing vision-language models with adversarial learning. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2203.11933 (2022)."},{"key":"e_1_3_3_2_6_2","unstructured":"James Betker Gabriel Goh Li Jing Tim Brooks Jianfeng Wang Linjie Li Long Ouyang Juntang Zhuang Joyce Lee Yufei Guo et\u00a0al. 2023. Improving image generation with better captions. Computer Science. https:\/\/cdn. openai. com\/papers\/dall-e-3. pdf 2 3 (2023) 8."},{"key":"e_1_3_3_2_7_2","unstructured":"Mukul Bhutani Kevin Robinson Vinodkumar Prabhakaran Shachi Dave and Sunipa Dev. 2024. SeeGULL Multilingual: a Dataset of Geo-Culturally Situated Stereotypes. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2403.05696 (2024)."},{"key":"e_1_3_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3593013.3594095"},{"key":"e_1_3_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/3551624.3555290"},{"key":"e_1_3_3_2_10_2","unstructured":"Abeba Birhane Vinay\u00a0Uday Prabhu and Emmanuel Kahembwe. 2021. Multimodal datasets: misogyny pornography and malignant stereotypes. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2110.01963 (2021)."},{"key":"e_1_3_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10599-4_29"},{"key":"e_1_3_3_2_12_2","first-page":"1877","volume-title":"Advances in Neural Information Processing Systems","author":"Brown Tom","year":"2020","unstructured":"Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared\u00a0D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020. Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems, H.\u00a0Larochelle, M.\u00a0Ranzato, R.\u00a0Hadsell, M.F. Balcan, and H.\u00a0Lin (Eds.), Vol.\u00a033. Curran Associates, Inc., 1877\u20131901."},{"key":"e_1_3_3_2_13_2","unstructured":"Tom\u00a0B Brown. 2020. Language models are few-shot learners. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2005.14165 (2020)."},{"key":"e_1_3_3_2_14_2","unstructured":"Rodney\u00a0GS Carter. 2006. Of things said and unsaid: Power archival silences and power in silence. Archivaria (2006) 215\u2013233."},{"key":"e_1_3_3_2_15_2","unstructured":"Cartografias da Internet. 2025. Cartografias da Internet. https:\/\/www.cartografiasdainternet.org\/en\/ [Accessed 13 January 2025]."},{"key":"e_1_3_3_2_16_2","volume-title":"ICLR","author":"Cho Jaemin","year":"2024","unstructured":"Jaemin Cho, Yushi Hu, Roopal Garg, Peter Anderson, Ranjay Krishna, Jason Baldridge, Mohit Bansal, Jordi Pont-Tuset, and Su Wang. 2024. Davidsonian Scene Graph: Improving Reliability in Fine-Grained Evaluation for Text-to-Image Generation. In ICLR."},{"key":"e_1_3_3_2_17_2","unstructured":"CompaniesMarketCap. 2024. Largest Internet Companies by Market Cap. https:\/\/companiesmarketcap.com\/internet\/largest-internet-companies-by-market-cap\/ Accessed: 2024-06-04."},{"key":"e_1_3_3_2_18_2","doi-asserted-by":"crossref","unstructured":"Ann Copestake Lucy Duggan Aurelie Herbelot Amira Moeding and Eva von Redecker. 2024. LLMs as supersloppers. (2024).","DOI":"10.33774\/coe-2024-dx12p"},{"key":"e_1_3_3_2_19_2","first-page":"52","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition workshops","author":"De\u00a0Vries Terrance","year":"2019","unstructured":"Terrance De\u00a0Vries, Ishan Misra, Changhan Wang, and Laurens Van\u00a0der Maaten. 2019. Does object recognition work for everyone?. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition workshops. 52\u201359."},{"key":"e_1_3_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/3617694.3623261"},{"key":"e_1_3_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_3_2_22_2","unstructured":"Terrance DeVries Adriana Romero Luis Pineda Graham\u00a0W Taylor and Michal Drozdzal. 2019. On the evaluation of conditional GANs. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1907.08175 (2019)."},{"key":"e_1_3_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordhb\/9780190460518.001.0001"},{"key":"e_1_3_3_2_24_2","unstructured":"Dan Friedman and Adji\u00a0Bousso Dieng. 2023. The Vendi Score: A Diversity Evaluation Metric for Machine Learning. arxiv:https:\/\/arXiv.org\/abs\/2210.02410\u00a0[cs.LG] https:\/\/arxiv.org\/abs\/2210.02410"},{"key":"e_1_3_3_2_25_2","unstructured":"William Gaviria\u00a0Rojas Sudnya Diamos Keertan Kini David Kanter Vijay Janapa\u00a0Reddi and Cody Coleman. 2022. The Dollar Street dataset: Images representing the geographic and socioeconomic diversity of the world. Advances in Neural Information Processing Systems 35 (2022) 12979\u201312990."},{"key":"e_1_3_3_2_26_2","unstructured":"Melissa Hall Candace Ross Adina Williams Nicolas Carion Michal Drozdzal and Adriana\u00a0Romero Soriano. 2024. DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic Diversity. arxiv:https:\/\/arXiv.org\/abs\/2308.06198\u00a0[cs.CV] https:\/\/arxiv.org\/abs\/2308.06198"},{"key":"e_1_3_3_2_27_2","unstructured":"Melissa Hall Laurens van\u00a0der Maaten Laura Gustafson Maxwell Jones and Aaron Adcock. 2022. A systematic study of bias amplification. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2201.11706 (2022)."},{"key":"e_1_3_3_2_28_2","unstructured":"Siobhan\u00a0Mackenzie Hall Samantha Dalal Raesetje Sefala Foutse Yuehgoh Aisha Alaagib Imane Hamzaoui Shu Ishida Jabez Magomere Lauren Crais Aya Salama et\u00a0al. 2025. The Human Labour of Data Work: Capturing Cultural Diversity through World Wide Dishes. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2502.05961 (2025)."},{"key":"e_1_3_3_2_29_2","unstructured":"Siobhan\u00a0Mackenzie Hall Fernanda Gon\u00e7alves\u00a0Abrantes Hanwen Zhu Grace Sodunke Aleksandar Shtedritski and Hannah\u00a0Rose Kirk. 2024. Visogender: A dataset for benchmarking gender bias in image-text pronoun resolution. Advances in Neural Information Processing Systems 36 (2024)."},{"key":"e_1_3_3_2_30_2","doi-asserted-by":"crossref","unstructured":"J Hardy. 2019. How the design of social technology fails rural America. DIS\u201919 Companion: Companion Publication of the 2019 on Designing Interactive Systems Conference 2019 Companion 189-193.","DOI":"10.1145\/3301019.3323906"},{"key":"e_1_3_3_2_31_2","unstructured":"Daniel Hershcovich and Laura Cabello. 2023. ChatGPT promotes American norms and values. https:\/\/news.ku.dk\/all_news\/2023\/07\/chatgpt-promotes-american-norms-and-values\/ University of Copenhagen."},{"key":"e_1_3_3_2_32_2","doi-asserted-by":"crossref","unstructured":"Jack Hessel Ari Holtzman Maxwell Forbes Ronan\u00a0Le Bras and Yejin Choi. 2021. Clipscore: A reference-free evaluation metric for image captioning. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2104.08718 (2021).","DOI":"10.18653\/v1\/2021.emnlp-main.595"},{"key":"e_1_3_3_2_33_2","unstructured":"Martin Heusel Hubert Ramsauer Thomas Unterthiner Bernhard Nessler and Sepp Hochreiter. 2017. Gans trained by a two time-scale update rule converge to a local nash equilibrium. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/3600211.3604662"},{"key":"e_1_3_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01866"},{"key":"e_1_3_3_2_36_2","unstructured":"Ben Hutchinson Jason Baldridge and Vinodkumar Prabhakaran. 2022. Underspecification in scene description-to-depiction tasks. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2210.05815 (2022)."},{"key":"e_1_3_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445901"},{"key":"e_1_3_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/8435.001.0001"},{"key":"e_1_3_3_2_39_2","unstructured":"Akshita Jha Vinodkumar Prabhakaran Remi Denton Sarah Laszlo Shachi Dave Rida Qadri Chandan\u00a0K Reddy and Sunipa Dev. 2024. Beyond the Surface: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2401.06310 (2024)."},{"key":"e_1_3_3_2_40_2","unstructured":"Nithish Kannen Arif Ahmad Marco Andreetto Vinodkumar Prabhakaran Utsav Prabhu Adji\u00a0Bousso Dieng Pushpak Bhattacharyya and Shachi Dave. 2024. Beyond aesthetics: Cultural competence in text-to-image models. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2407.06863 (2024)."},{"key":"e_1_3_3_2_41_2","unstructured":"Tuomas Kynk\u00e4\u00e4nniemi Tero Karras Samuli Laine Jaakko Lehtinen and Timo Aila. 2019. Improved precision and recall metric for assessing generative models. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.13633554"},{"key":"e_1_3_3_2_43_2","unstructured":"Tony Lee Michihiro Yasunaga Chenlin Meng Yifan Mai Joon\u00a0Sung Park Agrim Gupta Yunzhi Zhang Deepak Narayanan Hannah Teufel Marco Bellagente et\u00a0al. 2024. Holistic evaluation of text-to-image models. 36 (2024)."},{"key":"e_1_3_3_2_44_2","volume-title":"NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following","author":"Liu Haotian","year":"2023","unstructured":"Haotian Liu, Chunyuan Li, Yuheng Li, and Yong\u00a0Jae Lee. 2023. Improved Baselines with Visual Instruction Tuning. In NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following. https:\/\/openreview.net\/forum?id=yx3Hkx5ved"},{"key":"e_1_3_3_2_45_2","unstructured":"Haotian Liu Chunyuan Li Qingyang Wu and Yong\u00a0Jae Lee. 2024. Visual instruction tuning. Advances in neural information processing systems 36 (2024)."},{"key":"e_1_3_3_2_46_2","unstructured":"Shayne Longpre Nikhil Singh Manuel Cherep Kushagra Tiwary Joanna Materzynska William Brannon Robert Mahari Naana Obeng-Marnu Manan Dey Mohammed Hamdy et\u00a0al. 2024. Bridging the Data Provenance Gap Across Text Speech and Video. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2412.17847 (2024)."},{"key":"e_1_3_3_2_47_2","unstructured":"Alexandra\u00a0Sasha Luccioni Christopher Akiki Margaret Mitchell and Yacine Jernite. 2023. Stable bias: Analyzing societal representations in diffusion models. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2303.11408 (2023)."},{"key":"e_1_3_3_2_48_2","unstructured":"Javier Marin Aritro Biswas Ferda Ofli Nicholas Hynes Amaia Salvador Yusuf Aytar Ingmar Weber and Antonio Torralba. 2018. Recipe1M+: a dataset for learning cross-modal embeddings for cooking recipes and food images. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1810.06553 (2018)."},{"key":"e_1_3_3_2_49_2","volume-title":"51st Annual Hawai\u2019i International Conference on System Sciences","author":"Mitchell Erica","year":"2018","unstructured":"Erica Mitchell, Kevin\u00a0G Crowston, and Carsten Oesterlund. 2018. Coordinating advanced crowd work: Extending citizen science. In 51st Annual Hawai\u2019i International Conference on System Sciences."},{"key":"e_1_3_3_2_50_2","doi-asserted-by":"crossref","unstructured":"Deirdre\u00a0K Mulligan Joshua\u00a0A Kroll Nitin Kohli and Richmond\u00a0Y Wong. 2019. This thing called fairness: Disciplinary confusion realizing a value in technology. Proceedings of the ACM on Human-Computer Interaction 3 CSCW (2019) 1\u201336.","DOI":"10.1145\/3359221"},{"key":"e_1_3_3_2_51_2","doi-asserted-by":"publisher","unstructured":"Esther Mwema and Abeba Birhane. 2025. Undersea cables in Africa: The new frontiers of digital colonialism. First Monday 29 4 (2025). https:\/\/doi.org\/10.5210\/fm.v29i4.13637 [Accessed 13 January 2025].","DOI":"10.5210\/fm.v29i4.13637"},{"key":"e_1_3_3_2_52_2","series-title":"Proceedings of Machine Learning Research","first-page":"7176","volume-title":"Proceedings of the 37th International Conference on Machine Learning","volume":"119","author":"Naeem Muhammad\u00a0Ferjad","year":"2020","unstructured":"Muhammad\u00a0Ferjad Naeem, Seong\u00a0Joon Oh, Youngjung Uh, Yunjey Choi, and Jaejun Yoo. 2020. Reliable Fidelity and Diversity Metrics for Generative Models. In Proceedings of the 37th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0119), Hal\u00a0Daum\u00e9 III and Aarti Singh (Eds.). PMLR, 7176\u20137185. https:\/\/proceedings.mlr.press\/v119\/naeem20a.html"},{"key":"e_1_3_3_2_53_2","unstructured":"Quan Nguyen and Adji\u00a0Bousso Dieng. 2024. Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design. arxiv:https:\/\/arXiv.org\/abs\/2405.02449\u00a0[stat.ML] https:\/\/arxiv.org\/abs\/2405.02449"},{"key":"e_1_3_3_2_54_2","unstructured":"Library of Congress. 2024. Alpha-3 codes arranged alphabetically by English name of Language\u2014Codes for the representation of names of languages. https:\/\/www.loc.gov\/standards\/iso639-2\/php\/English_list.php. Accessed: 2024-05-28."},{"key":"e_1_3_3_2_55_2","unstructured":"Open Future. 2025. How Wikipedia Can Shape the Future of AI. https:\/\/openfuture.eu\/blog\/how-wikipedia-can-shape-the-future-of-ai\/ [Accessed 13 January 2025]."},{"key":"e_1_3_3_2_56_2","unstructured":"OpenAI. 2022. ChatGPT. https:\/\/openai.com\/blog\/chatgpt."},{"key":"e_1_3_3_2_57_2","unstructured":"OpenAI. 2022. DALL\u00b7E now available without waitlist. https:\/\/openai.com\/index\/dall-e-now-available-without-waitlist\/ Accessed: 2024-05-28."},{"key":"e_1_3_3_2_58_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01372"},{"key":"e_1_3_3_2_59_2","unstructured":"The Good\u00a0Robot Podcast. 2025. Margaret Mitchell on Large Language Models and Misogyny in Tech. https:\/\/podcasts.apple.com\/fr\/podcast\/margaret-mitchell-on-large-language-models-and\/id1570237963?i=1000569683327 [Accessed 13 January 2025]."},{"key":"e_1_3_3_2_60_2","unstructured":"Ang\u00e9line Pouget Lucas Beyer Emanuele Bugliarello Xiao Wang Andreas\u00a0Peter Steiner Xiaohua Zhai and Ibrahim Alabdulmohsin. 2024. No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2405.13777 (2024)."},{"key":"e_1_3_3_2_61_2","first-page":"8748","volume-title":"International conference on machine learning","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong\u00a0Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et\u00a0al. 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748\u20138763."},{"key":"e_1_3_3_2_62_2","unstructured":"Colin Raffel Noam Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li and Peter\u00a0J Liu. 2020. Exploring the limits of transfer learning with a unified text-to-text transformer. Journal of machine learning research 21 140 (2020) 1\u201367."},{"key":"e_1_3_3_2_63_2","unstructured":"Aditya Ramesh Prafulla Dhariwal Alex Nichol Casey Chu and Mark Chen. 2022. Hierarchical text-conditional image generation with clip latents. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2204.06125 1 2 (2022) 3."},{"key":"e_1_3_3_2_64_2","volume-title":"ChatGPT Sets Record for Fastest Growing User Base - Analyst Note","year":"2023","unstructured":"Reuters. 2023. ChatGPT Sets Record for Fastest Growing User Base - Analyst Note. https:\/\/www.reuters.com\/technology\/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01\/ Accessed: 2024-09-10."},{"key":"e_1_3_3_2_65_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"e_1_3_3_2_66_2","unstructured":"David Romero Chenyang Lyu Haryo\u00a0Akbarianto Wibowo Teresa Lynn Injy Hamed Aditya\u00a0Nanda Kishore Aishik Mandal Alina Dragonetti Artem Abzaliev Atnafu\u00a0Lambebo Tonja et\u00a0al. 2024. Cvqa: Culturally-diverse multilingual visual question answering benchmark. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2406.05967 (2024)."},{"key":"e_1_3_3_2_67_2","doi-asserted-by":"crossref","unstructured":"Paul R\u00f6ttger Hannah\u00a0Rose Kirk Bertie Vidgen Giuseppe Attanasio Federico Bianchi and Dirk Hovy. 2023. Xstest: A test suite for identifying exaggerated safety behaviours in large language models. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2308.01263 (2023).","DOI":"10.18653\/v1\/2024.naacl-long.301"},{"key":"e_1_3_3_2_68_2","unstructured":"Chitwan Saharia William Chan Saurabh Saxena Lala Li Jay Whang Emily\u00a0L Denton Kamyar Ghasemipour Raphael Gontijo\u00a0Lopes Burcu Karagol\u00a0Ayan Tim Salimans et\u00a0al. 2022. Photorealistic text-to-image diffusion models with deep language understanding. Advances in neural information processing systems 35 (2022) 36479\u201336494."},{"key":"e_1_3_3_2_69_2","unstructured":"Chitwan Saharia William Chan Saurabh Saxena Lala Li Jay Whang Emily\u00a0L Denton Kamyar Ghasemipour Raphael Gontijo\u00a0Lopes Burcu Karagol\u00a0Ayan Tim Salimans et\u00a0al. 2022. Photorealistic text-to-image diffusion models with deep language understanding. Advances in neural information processing systems 35 (2022) 36479\u201336494."},{"key":"e_1_3_3_2_70_2","unstructured":"Mehdi\u00a0SM Sajjadi Olivier Bachem Mario Lucic Olivier Bousquet and Sylvain Gelly. 2018. Assessing generative models via precision and recall. Advances in neural information processing systems 31 (2018)."},{"key":"e_1_3_3_2_71_2","unstructured":"Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford and Xi Chen. 2016. Improved techniques for training gans. Advances in neural information processing systems 29 (2016)."},{"key":"e_1_3_3_2_72_2","unstructured":"Christoph Schuhmann Romain Beaumont Richard Vencu Cade Gordon Ross Wightman Mehdi Cherti Theo Coombes Aarush Katta Clayton Mullis Mitchell Wortsman et\u00a0al. 2022. Laion-5b: An open large-scale dataset for training next generation image-text models. Advances in Neural Information Processing Systems 35 (2022) 25278\u201325294."},{"key":"e_1_3_3_2_73_2","unstructured":"Christoph Schuhmann Richard Vencu Romain Beaumont Robert Kaczmarczyk Clayton Mullis Aarush Katta Theo Coombes Jenia Jitsev and Aran Komatsuzaki. 2021. Laion-400m: Open dataset of clip-filtered 400 million image-text pairs. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2111.02114 (2021)."},{"key":"e_1_3_3_2_74_2","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287598"},{"key":"e_1_3_3_2_75_2","unstructured":"Shreya Shankar Yoni Halpern Eric Breck James Atwood Jimbo Wilson and D Sculley. 2017. No classification without representation: Assessing geodiversity issues in open data sets for the developing world. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1711.08536 (2017)."},{"key":"e_1_3_3_2_76_2","unstructured":"Shivalika Singh Freddie Vargus Daniel D\u2019souza B\u00f6rje\u00a0F Karlsson Abinaya Mahendiran Wei-Yin Ko Herumb Shandilya Jay Patel Deividas Mataciunas Laura O\u2019Mahony et\u00a0al. 2024. Aya dataset: An open-access collection for multilingual instruction tuning. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2402.06619 (2024)."},{"key":"e_1_3_3_2_77_2","doi-asserted-by":"crossref","unstructured":"Athula Sumathipala Sisira Siribaddana and Vikram Patel. 2004. Under-representation of developing countries in the research literature: ethical issues arising from a survey of five leading medical journals. BMC medical ethics 5 (2004) 1\u20136.","DOI":"10.1186\/1472-6939-5-5"},{"key":"e_1_3_3_2_78_2","unstructured":"The World Bank. 2023. Individuals using the Internet (% of population). https:\/\/databank.worldbank.org\/reports.aspx?source=2&series=IT.NET.USER.ZS&country=#. Accessed: 2025-01-06."},{"key":"e_1_3_3_2_79_2","unstructured":"Hanna Wallach Meera Desai Nicholas Pangakis A\u00a0Feder Cooper Angelina Wang Solon Barocas Alexandra Chouldechova Chad Atalla Su\u00a0Lin Blodgett Emily Corvi et\u00a0al. 2024. Evaluating Generative AI Systems is a Social Science Measurement Challenge. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2411.10939 (2024)."},{"key":"e_1_3_3_2_80_2","unstructured":"Laura Weidinger John Mellor Maribeth Rauh Conor Griffin Jonathan Uesato Po-Sen Huang Myra Cheng Mia Glaese Borja Balle Atoosa Kasirzadeh et\u00a0al. 2021. Ethical and social risks of harm from language models. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2112.04359 (2021)."},{"key":"e_1_3_3_2_81_2","unstructured":"Laura Weidinger Maribeth Rauh Nahema Marchal Arianna Manzini Lisa\u00a0Anne Hendricks Juan Mateos-Garcia Stevie Bergman Jackie Kay Conor Griffin Ben Bariach et\u00a0al. 2023. Sociotechnical safety evaluation of generative ai systems. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2310.11986 (2023)."},{"key":"e_1_3_3_2_82_2","unstructured":"Wikimedia Foundation. 2023. Wikipedia\u2019s Value in the Age of Generative AI. https:\/\/wikimediafoundation.org\/news\/2023\/07\/12\/wikipedias-value-in-the-age-of-generative-ai\/ [Accessed 13 January 2025]."},{"key":"e_1_3_3_2_83_2","unstructured":"Genta\u00a0Indra Winata Frederikus Hudi Patrick\u00a0Amadeus Irawan David Anugraha Rifki\u00a0Afina Putri Yutong Wang Adam Nohejl Ubaidillah\u00a0Ariq Prathama Nedjma Ousidhoum Afifa Amriani et\u00a0al. 2024. WorldCuisines: A massive-scale benchmark for multilingual and multicultural visual question answering on global cuisines. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2410.12705 (2024)."},{"key":"e_1_3_3_2_84_2","unstructured":"Lianmin Zheng Liangsheng Yin Zhiqiang Xie Chuyue Sun Jeff Huang Cody\u00a0Hao Yu Shiyi Cao Christos Kozyrakis Ion Stoica Joseph\u00a0E. Gonzalez Clark Barrett and Ying Sheng. 2024. SGLang: Efficient Execution of Structured Language Model Programs. arxiv:https:\/\/arXiv.org\/abs\/2312.07104\u00a0[cs.AI] https:\/\/arxiv.org\/abs\/2312.07104"}],"event":{"name":"FAccT '25: The 2025 ACM Conference on Fairness, Accountability, and Transparency","location":"Athens Greece","acronym":"FAccT '25"},"container-title":["Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3715275.3732019","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T11:22:29Z","timestamp":1750764149000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715275.3732019"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,23]]},"references-count":83,"alternative-id":["10.1145\/3715275.3732019","10.1145\/3715275"],"URL":"https:\/\/doi.org\/10.1145\/3715275.3732019","relation":{},"subject":[],"published":{"date-parts":[[2025,6,23]]},"assertion":[{"value":"2025-06-23","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}