{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T21:24:47Z","timestamp":1771104287898,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":69,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,29]],"date-time":"2023-10-29T00:00:00Z","timestamp":1698537600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"King's China Scholarship Council (K-CSC) PhD Scholarship programme"},{"name":"NVIDIA Academic Hardware Grant Program"},{"name":"EPSRC","award":["EP\/V010875\/1"],"award-info":[{"award-number":["EP\/V010875\/1"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,29]]},"DOI":"10.1145\/3607865.3616175","type":"proceedings-article","created":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T18:12:36Z","timestamp":1697566356000},"page":"39-50","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Generalised Bias Mitigation for Personality Computing"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3588-2723","authenticated-orcid":false,"given":"Jian","family":"Jiang","sequence":"first","affiliation":[{"name":"King's College London, London, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8436-7343","authenticated-orcid":false,"given":"Viswonathan","family":"Manoranjan","sequence":"additional","affiliation":[{"name":"New York University Abu Dhabi, Abu Dhabi, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6971-5264","authenticated-orcid":false,"given":"Hanan","family":"Salam","sequence":"additional","affiliation":[{"name":"New York University Abu Dhabi, Abu Dhabi, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7213-6359","authenticated-orcid":false,"given":"Oya","family":"Celiktutan","sequence":"additional","affiliation":[{"name":"King's College London, London, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,10,29]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"International Conference on Machine Learning. PMLR, 60--69","author":"Agarwal Alekh","year":"2018","unstructured":"Alekh Agarwal , Alina Beygelzimer , Miroslav Dud\u00edk , John Langford , and Hanna Wallach . 2018 . A reductions approach to fair classification . In International Conference on Machine Learning. PMLR, 60--69 . Alekh Agarwal, Alina Beygelzimer, Miroslav Dud\u00edk, John Langford, and Hanna Wallach. 2018. A reductions approach to fair classification. In International Conference on Machine Learning. PMLR, 60--69."},{"key":"e_1_3_2_1_2_1","volume-title":"International Conference on Machine Learning. PMLR, 120--129","author":"Agarwal Alekh","year":"2019","unstructured":"Alekh Agarwal , Miroslav Dud\u00edk , and Zhiwei Steven Wu . 2019 . Fair regression: Quantitative definitions and reduction-based algorithms . In International Conference on Machine Learning. PMLR, 120--129 . Alekh Agarwal, Miroslav Dud\u00edk, and Zhiwei Steven Wu. 2019. Fair regression: Quantitative definitions and reduction-based algorithms. In International Conference on Machine Learning. PMLR, 120--129."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1147\/JRD.2019.2942287"},{"key":"e_1_3_2_1_4_1","volume-title":"Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv preprint arXiv:1308.3432","author":"Bengio Yoshua","year":"2013","unstructured":"Yoshua Bengio , Nicholas L\u00e9onard , and Aaron Courville . 2013. Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv preprint arXiv:1308.3432 ( 2013 ). Yoshua Bengio, Nicholas L\u00e9onard, and Aaron Courville. 2013. Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv preprint arXiv:1308.3432 (2013)."},{"key":"e_1_3_2_1_5_1","volume-title":"Yash Bhalgat, Wonsuk Yang, Hannah Rose Kirk, Aleksandar Shtedritski, and Max Bain.","author":"Berg Hugo","year":"2022","unstructured":"Hugo Berg , Siobhan Mackenzie Hall , Yash Bhalgat, Wonsuk Yang, Hannah Rose Kirk, Aleksandar Shtedritski, and Max Bain. 2022 . A prompt array keeps the bias away: Debiasing vision-language models with adversarial learning. arXiv preprint arXiv:2203.11933 (2022). Hugo Berg, Siobhan Mackenzie Hall, Yash Bhalgat, Wonsuk Yang, Hannah Rose Kirk, Aleksandar Shtedritski, and Max Bain. 2022. A prompt array keeps the bias away: Debiasing vision-language models with adversarial learning. arXiv preprint arXiv:2203.11933 (2022)."},{"key":"e_1_3_2_1_6_1","volume-title":"Proceedings of the 1st Conference on Fairness, Accountability and Transparency. 77--91","author":"Buolamwini Joy","year":"2018","unstructured":"Joy Buolamwini and Timnit Gebru . 2018 . Gender shades: Intersectional accuracy disparities in commercial gender classification . In Proceedings of the 1st Conference on Fairness, Accountability and Transparency. 77--91 . Joy Buolamwini and Timnit Gebru. 2018. Gender shades: Intersectional accuracy disparities in commercial gender classification. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency. 77--91."},{"key":"e_1_3_2_1_7_1","volume-title":"Semantics derived automatically from language corpora contain human-like biases. Science 356, 6334","author":"Caliskan Aylin","year":"2017","unstructured":"Aylin Caliskan , Joanna J Bryson , and Arvind Narayanan . 2017. Semantics derived automatically from language corpora contain human-like biases. Science 356, 6334 ( 2017 ), 183--186. Aylin Caliskan, Joanna J Bryson, and Arvind Narayanan. 2017. Semantics derived automatically from language corpora contain human-like biases. Science 356, 6334 (2017), 183--186."},{"key":"e_1_3_2_1_8_1","volume-title":"Fairness in machine learning: A survey. arXiv preprint arXiv:2010.04053","author":"Caton Simon","year":"2020","unstructured":"Simon Caton and Christian Haas . 2020. Fairness in machine learning: A survey. arXiv preprint arXiv:2010.04053 ( 2020 ). Simon Caton and Christian Haas. 2020. Fairness in machine learning: A survey. arXiv preprint arXiv:2010.04053 (2020)."},{"key":"e_1_3_2_1_9_1","volume-title":"Automatic prediction of impressions in time and across varying context: Personality, attractiveness and likeability","author":"Celiktutan Oya","year":"2015","unstructured":"Oya Celiktutan and Hatice Gunes . 2015. Automatic prediction of impressions in time and across varying context: Personality, attractiveness and likeability . IEEE transactions on affective computing 8, 1 ( 2015 ), 29--42. Oya Celiktutan and Hatice Gunes. 2015. Automatic prediction of impressions in time and across varying context: Personality, attractiveness and likeability. IEEE transactions on affective computing 8, 1 (2015), 29--42."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287586"},{"key":"e_1_3_2_1_11_1","volume-title":"Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structurebased virtual screening. PLOS ONE 14, 8 (08","author":"Chen Lieyang","year":"2019","unstructured":"Lieyang Chen , Anthony Cruz , Steven Ramsey , Callum J. Dickson , Jose S. Duca , Viktor Hornak , David R. Koes , and Tom Kurtzman . 2019. Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structurebased virtual screening. PLOS ONE 14, 8 (08 2019 ), 1--22. https:\/\/doi.org\/10.1371\/ journal.pone.0220113 Lieyang Chen, Anthony Cruz, Steven Ramsey, Callum J. Dickson, Jose S. Duca, Viktor Hornak, David R. Koes, and Tom Kurtzman. 2019. Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structurebased virtual screening. PLOS ONE 14, 8 (08 2019), 1--22. https:\/\/doi.org\/10.1371\/ journal.pone.0220113"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3536221.3556569"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2022.3181033"},{"key":"e_1_3_2_1_15_1","volume-title":"Huansheng Ning, and Erik Cambria.","author":"Dhelim Sahraoui","year":"2022","unstructured":"Sahraoui Dhelim , Nyothiri Aung , Mohammed Amine Bouras , Huansheng Ning, and Erik Cambria. 2022 . A survey on personality-aware recommendation systems. Artificial Intelligence Review ( 2022), 1--46. Sahraoui Dhelim, Nyothiri Aung, Mohammed Amine Bouras, Huansheng Ning, and Erik Cambria. 2022. A survey on personality-aware recommendation systems. Artificial Intelligence Review (2022), 1--46."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/2090236.2090255"},{"key":"e_1_3_2_1_17_1","volume-title":"Conference on fairness, accountability and transparency. PMLR, 119--133","author":"Dwork Cynthia","year":"2018","unstructured":"Cynthia Dwork , Nicole Immorlica , Adam Tauman Kalai , and Max Leiserson . 2018 . Decoupled classifiers for group-fair and efficient machine learning . In Conference on fairness, accountability and transparency. PMLR, 119--133 . Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, and Max Leiserson. 2018. Decoupled classifiers for group-fair and efficient machine learning. In Conference on fairness, accountability and transparency. PMLR, 119--133."},{"key":"e_1_3_2_1_18_1","unstructured":"William Falcon et al. 2019. PyTorch Lightning. GitHub. Note: https:\/\/github.com\/PyTorchLightning\/pytorch-lightning 3 (2019).  William Falcon et al. 2019. PyTorch Lightning. GitHub. Note: https:\/\/github.com\/PyTorchLightning\/pytorch-lightning 3 (2019)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783311"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2020.3032461"},{"key":"e_1_3_2_1_21_1","volume-title":"Perception of Speaker Personality Traits Using Speech Signals (CHI EA '18)","author":"Gilpin Leilani H.","year":"1885","unstructured":"Leilani H. Gilpin , Danielle M. Olson , and Tarfah Alrashed . 2018. Perception of Speaker Personality Traits Using Speech Signals (CHI EA '18) . Association for Computing Machinery , New York, NY, USA , 1--6. https:\/\/doi.org\/10.1145\/ 3170427.3 1885 57 Leilani H. Gilpin, Danielle M. Olson, and Tarfah Alrashed. 2018. Perception of Speaker Personality Traits Using Speech Signals (CHI EA '18). Association for Computing Machinery, New York, NY, USA, 1--6. https:\/\/doi.org\/10.1145\/ 3170427.3188557"},{"key":"e_1_3_2_1_22_1","unstructured":"Jianzhu Guo Xiangyu Zhu and Zhen Lei. 2018. 3DDFA. https:\/\/github.com\/ cleardusk\/3DDFA.  Jianzhu Guo Xiangyu Zhu and Zhen Lei. 2018. 3DDFA. https:\/\/github.com\/ cleardusk\/3DDFA."},{"key":"e_1_3_2_1_23_1","volume-title":"Proceedings, Part XIX. Springer, 152--168","author":"Guo Jianzhu","year":"2020","unstructured":"Jianzhu Guo , Xiangyu Zhu , Yang Yang , Fan Yang , Zhen Lei , and Stan Z Li . 2020 . Towards fast, accurate and stable 3d dense face alignment. In Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020 , Proceedings, Part XIX. Springer, 152--168 . Jianzhu Guo, Xiangyu Zhu, Yang Yang, Fan Yang, Zhen Lei, and Stan Z Li. 2020. Towards fast, accurate and stable 3d dense face alignment. In Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part XIX. Springer, 152--168."},{"key":"e_1_3_2_1_24_1","volume-title":"Improving multimodal fusion with hierarchical mutual information maximization for multimodal sentiment analysis. arXiv preprint arXiv:2109.00412","author":"Han Wei","year":"2021","unstructured":"Wei Han , Hui Chen , and Soujanya Poria . 2021. Improving multimodal fusion with hierarchical mutual information maximization for multimodal sentiment analysis. arXiv preprint arXiv:2109.00412 ( 2021 ). Wei Han, Hui Chen, and Soujanya Poria. 2021. Improving multimodal fusion with hierarchical mutual information maximization for multimodal sentiment analysis. arXiv preprint arXiv:2109.00412 (2021)."},{"key":"e_1_3_2_1_25_1","volume-title":"International conference on machine learning. PMLR, 4651--4664","author":"Jaegle Andrew","year":"2021","unstructured":"Andrew Jaegle , Felix Gimeno , Andy Brock , Oriol Vinyals , Andrew Zisserman , and Joao Carreira . 2021 . Perceiver: General perception with iterative attention . In International conference on machine learning. PMLR, 4651--4664 . Andrew Jaegle, Felix Gimeno, Andy Brock, Oriol Vinyals, Andrew Zisserman, and Joao Carreira. 2021. Perceiver: General perception with iterative attention. In International conference on machine learning. PMLR, 4651--4664."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2014.2339834"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00144"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-011-0463-8"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2017.09.064"},{"key":"e_1_3_2_1_30_1","volume-title":"Multimodal personality trait analysis for explainable modeling of job interview decisions. Explainable and Interpretable Models in Computer Vision and Machine Learning","author":"Kaya Heysem","year":"2018","unstructured":"Heysem Kaya and Albert Ali Salah . 2018. Multimodal personality trait analysis for explainable modeling of job interview decisions. Explainable and Interpretable Models in Computer Vision and Machine Learning ( 2018 ), 255--275. Heysem Kaya and Albert Ali Salah. 2018. Multimodal personality trait analysis for explainable modeling of job interview decisions. Explainable and Interpretable Models in Computer Vision and Machine Learning (2018), 255--275."},{"key":"e_1_3_2_1_31_1","volume-title":"MEDINFO 2019: Health and Wellbeing e-Networks for All. IOS Press, 974--978","author":"Kim Isaac E","year":"2019","unstructured":"Isaac E Kim Jr and Indra Neil Sarkar . 2019 . Racial representation disparity of population-level genomic sequencing efforts . In MEDINFO 2019: Health and Wellbeing e-Networks for All. IOS Press, 974--978 . Isaac E Kim Jr and Indra Neil Sarkar. 2019. Racial representation disparity of population-level genomic sequencing efforts. In MEDINFO 2019: Health and Wellbeing e-Networks for All. IOS Press, 974--978."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3468507.3468518"},{"key":"e_1_3_2_1_33_1","volume-title":"A survey on personalized affective computing in human-machine interaction. arXiv preprint arXiv:2304.00377","author":"Li Jialin","year":"2023","unstructured":"Jialin Li , Alia Waleed , and Hanan Salam . 2023. A survey on personalized affective computing in human-machine interaction. arXiv preprint arXiv:2304.00377 ( 2023 ). Jialin Li, Alia Waleed, and Hanan Salam. 2023. A survey on personalized affective computing in human-machine interaction. arXiv preprint arXiv:2304.00377 (2023)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2020.2973158"},{"key":"e_1_3_2_1_35_1","volume-title":"Multitask learning for emotion and personality detection. arXiv preprint arXiv:2101.02346","author":"Li Yang","year":"2021","unstructured":"Yang Li , Amirmohammad Kazameini , Yash Mehta , and Erik Cambria . 2021. Multitask learning for emotion and personality detection. arXiv preprint arXiv:2101.02346 ( 2021 ). Yang Li, Amirmohammad Kazameini, Yash Mehta, and Erik Cambria. 2021. Multitask learning for emotion and personality detection. arXiv preprint arXiv:2101.02346 (2021)."},{"key":"e_1_3_2_1_36_1","volume-title":"An open-source benchmark of deep learning models for audio-visual apparent and self-reported personality recognition. arXiv preprint arXiv:2210.09138","author":"Liao Rongfan","year":"2022","unstructured":"Rongfan Liao , Siyang Song , and Hatice Gunes . 2022. An open-source benchmark of deep learning models for audio-visual apparent and self-reported personality recognition. arXiv preprint arXiv:2210.09138 ( 2022 ). Rongfan Liao, Siyang Song, and Hatice Gunes. 2022. An open-source benchmark of deep learning models for audio-visual apparent and self-reported personality recognition. arXiv preprint arXiv:2210.09138 (2022)."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/1081870.1081950"},{"key":"e_1_3_2_1_38_1","volume-title":"FERMI: Fair Empirical Risk Minimization via Exponential R\\'enyi Mutual Information. arXiv preprint arXiv:2102.12586","author":"Lowy Andrew","year":"2021","unstructured":"Andrew Lowy , Rakesh Pavan , Sina Baharlouei , Meisam Razaviyayn , and Ahmad Beirami . 2021 . FERMI: Fair Empirical Risk Minimization via Exponential R\\'enyi Mutual Information. arXiv preprint arXiv:2102.12586 (2021). Andrew Lowy, Rakesh Pavan, Sina Baharlouei, Meisam Razaviyayn, and Ahmad Beirami. 2021. FERMI: Fair Empirical Risk Minimization via Exponential R\\'enyi Mutual Information. arXiv preprint arXiv:2102.12586 (2021)."},{"key":"e_1_3_2_1_39_1","volume-title":"FNNC: Achieving Fairness through Neural Networks. arXiv:1811.00247 [cs.LG]","author":"Manisha Padala","year":"2020","unstructured":"Padala Manisha and Sujit Gujar . 2020 . FNNC: Achieving Fairness through Neural Networks. arXiv:1811.00247 [cs.LG] Padala Manisha and Sujit Gujar. 2020. FNNC: Achieving Fairness through Neural Networks. arXiv:1811.00247 [cs.LG]"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341161.3342915"},{"key":"e_1_3_2_1_41_1","volume-title":"Deep Learning for Emotion Recognition on Small Datasets Using Transfer Learning and Data Augmentation. In 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG","author":"Mollahosseini Ali","year":"2019","unstructured":"Ali Mollahosseini , Behzad Hasani , and Mohammad H Mahoor . 2019 . Deep Learning for Emotion Recognition on Small Datasets Using Transfer Learning and Data Augmentation. In 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019). IEEE, 1--8. Ali Mollahosseini, Behzad Hasani, and Mohammad H Mahoor. 2019. Deep Learning for Emotion Recognition on Small Datasets Using Transfer Learning and Data Augmentation. In 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019). IEEE, 1--8."},{"key":"e_1_3_2_1_42_1","volume-title":"Multi-Task Deep Neural Networks for Multimodal Personality Trait Prediction. In 2021 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 85--91","author":"Mujtaba Dena F","year":"2021","unstructured":"Dena F Mujtaba and Nihar R Mahapatra . 2021 . Multi-Task Deep Neural Networks for Multimodal Personality Trait Prediction. In 2021 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 85--91 . Dena F Mujtaba and Nihar R Mahapatra. 2021. Multi-Task Deep Neural Networks for Multimodal Personality Trait Prediction. In 2021 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 85--91."},{"key":"e_1_3_2_1_43_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning (Proceedings of Machine Learning Research","volume":"4682","author":"Nabi Razieh","year":"2019","unstructured":"Razieh Nabi , Daniel Malinsky , and Ilya Shpitser . 2019 . Learning Optimal Fair Policies . In Proceedings of the 36th International Conference on Machine Learning (Proceedings of Machine Learning Research , Vol. 97), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 4674-- 4682 . https:\/\/proceedings.mlr.press\/ v97\/nabi19a.html Razieh Nabi, Daniel Malinsky, and Ilya Shpitser. 2019. Learning Optimal Fair Policies. In Proceedings of the 36th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 97), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 4674--4682. https:\/\/proceedings.mlr.press\/ v97\/nabi19a.html"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11553"},{"key":"e_1_3_2_1_45_1","unstructured":"Cristina Palmero Germ\u00e1n Barquero Julio Junior Albert Clap\u00e9s Johnny N\u00fa\u00f1ez Cano David Jan\u00f3 Javier Selva Zejian Zhang David Saeteros P\u00e9rez David Gallardo-Pujol Georgina Guilera David Leiva Universitat Barcelona Spain Feng Xiaoxue Feng Jennifer He Wei-Wei Tu Thomas Moeslund and Sergio Escalera. 2022. ChaLearn LAP Challenges on Self-Reported Personality Recognition and Non-Verbal Behavior Forecasting During Social Dyadic Interactions: Dataset Design and Results. (04 2022).  Cristina Palmero Germ\u00e1n Barquero Julio Junior Albert Clap\u00e9s Johnny N\u00fa\u00f1ez Cano David Jan\u00f3 Javier Selva Zejian Zhang David Saeteros P\u00e9rez David Gallardo-Pujol Georgina Guilera David Leiva Universitat Barcelona Spain Feng Xiaoxue Feng Jennifer He Wei-Wei Tu Thomas Moeslund and Sergio Escalera. 2022. ChaLearn LAP Challenges on Self-Reported Personality Recognition and Non-Verbal Behavior Forecasting During Social Dyadic Interactions: Dataset Design and Results. (04 2022)."},{"key":"e_1_3_2_1_46_1","volume-title":"Personality computing: New frontiers in personality assessment. Social and personality psychology compass 15, 7","author":"Phan Le Vy","year":"2021","unstructured":"Le Vy Phan and John F Rauthmann . 2021. Personality computing: New frontiers in personality assessment. Social and personality psychology compass 15, 7 ( 2021 ), e12624. Le Vy Phan and John F Rauthmann. 2021. Personality computing: New frontiers in personality assessment. Social and personality psychology compass 15, 7 (2021), e12624."},{"key":"e_1_3_2_1_47_1","volume-title":"On fairness and calibration. Advances in neural information processing systems 30","author":"Pleiss Geoff","year":"2017","unstructured":"Geoff Pleiss , Manish Raghavan , Felix Wu , Jon Kleinberg , and Kilian Q Weinberger . 2017. On fairness and calibration. Advances in neural information processing systems 30 ( 2017 ). Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger. 2017. On fairness and calibration. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_48_1","volume-title":"Hugo Jair Escalante, and Sergio Escalera","author":"Ponce-L\u00f3pez V\u00edctor","year":"2016","unstructured":"V\u00edctor Ponce-L\u00f3pez , Baiyu Chen , Marc Oliu , Ciprian Corneanu , Albert Clap\u00e9s , Isabelle Guyon , Xavier Bar\u00f3 , Hugo Jair Escalante, and Sergio Escalera . 2016 . ChaLearn LAP 2016: First Round Challenge on First Impressions - Dataset and Results. In Computer Vision -- ECCV 2016 Workshops, Gang Hua and Herv\u00e9 J\u00e9gou (Eds.). Springer International Publishing , Cham, 400--418. V\u00edctor Ponce-L\u00f3pez, Baiyu Chen, Marc Oliu, Ciprian Corneanu, Albert Clap\u00e9s, Isabelle Guyon, Xavier Bar\u00f3, Hugo Jair Escalante, and Sergio Escalera. 2016. ChaLearn LAP 2016: First Round Challenge on First Impressions - Dataset and Results. In Computer Vision -- ECCV 2016 Workshops, Gang Hua and Herv\u00e9 J\u00e9gou (Eds.). Springer International Publishing, Cham, 400--418."},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.measen.2022.100655"},{"key":"e_1_3_2_1_50_1","volume-title":"Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084","author":"Reimers Nils","year":"2019","unstructured":"Nils Reimers and Iryna Gurevych . 2019 . Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084 (2019). Nils Reimers and Iryna Gurevych. 2019. Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084 (2019)."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-26387-3_43"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2023.3278707"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2016.2614525"},{"key":"e_1_3_2_1_54_1","volume-title":"Understanding Social Behavior in Dyadic and Small Group Interactions (Proceedings of Machine Learning Research","volume":"73","author":"Salam Hanan","year":"2022","unstructured":"Hanan Salam , Viswonathan Manoranjan , Jian Jiang , and Oya Celiktutan . 2022 . Learning Personalised Models for Automatic Self-Reported Personality Recognition . In Understanding Social Behavior in Dyadic and Small Group Interactions (Proceedings of Machine Learning Research , Vol. 173), Cristina Palmero, Julio C. S. Jacques Junior, Albert Clap\u00e9s, Isabelle Guyon, Wei-Wei Tu, Thomas B. Moeslund, and Sergio Escalera (Eds.). PMLR, 53-- 73 . Hanan Salam, Viswonathan Manoranjan, Jian Jiang, and Oya Celiktutan. 2022. Learning Personalised Models for Automatic Self-Reported Personality Recognition. In Understanding Social Behavior in Dyadic and Small Group Interactions (Proceedings of Machine Learning Research, Vol. 173), Cristina Palmero, Julio C. S. Jacques Junior, Albert Clap\u00e9s, Isabelle Guyon, Wei-Wei Tu, Thomas B. Moeslund, and Sergio Escalera (Eds.). PMLR, 53--73."},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.3390\/make4010011"},{"key":"e_1_3_2_1_56_1","volume-title":"Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (Proceedings of Machine Learning Research","volume":"2173","author":"Song Jiaming","year":"2019","unstructured":"Jiaming Song , Pratyusha Kalluri , Aditya Grover , Shengjia Zhao , and Stefano Ermon . 2019 . Learning Controllable Fair Representations . In Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (Proceedings of Machine Learning Research , Vol. 89), Kamalika Chaudhuri and Masashi Sugiyama (Eds.). PMLR, 2164-- 2173 . https:\/\/proceedings.mlr.press\/v89\/ song19a.html Jiaming Song, Pratyusha Kalluri, Aditya Grover, Shengjia Zhao, and Stefano Ermon. 2019. Learning Controllable Fair Representations. In Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics (Proceedings of Machine Learning Research, Vol. 89), Kamalika Chaudhuri and Masashi Sugiyama (Eds.). PMLR, 2164--2173. https:\/\/proceedings.mlr.press\/v89\/ song19a.html"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372837"},{"key":"e_1_3_2_1_58_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani , Noam Shazeer , Niki Parmar , Jakob Uszkoreit , Llion Jones , Aidan N Gomez , \"ukasz Kaiser, and Illia Polosukhin . 2017. Attention is all you need. Advances in neural information processing systems 30 ( 2017 ). Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \"ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2014.2330816"},{"key":"e_1_3_2_1_60_1","volume-title":"Achieving fairness through adversarial learning: an application to recidivism prediction. arXiv preprint arXiv:1807.00199","author":"Wadsworth Christina","year":"2018","unstructured":"Christina Wadsworth , Francesca Vera , and Chris Piech . 2018. Achieving fairness through adversarial learning: an application to recidivism prediction. arXiv preprint arXiv:1807.00199 ( 2018 ). Christina Wadsworth, Francesca Vera, and Chris Piech. 2018. Achieving fairness through adversarial learning: an application to recidivism prediction. arXiv preprint arXiv:1807.00199 (2018)."},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00541"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467326"},{"key":"e_1_3_2_1_63_1","volume-title":"Fairness-aware classification: Criterion, convexity, and bounds. arXiv preprint arXiv:1809.04737","author":"Wu Yongkai","year":"2018","unstructured":"Yongkai Wu , Lu Zhang , and Xintao Wu. 2018. Fairness-aware classification: Criterion, convexity, and bounds. arXiv preprint arXiv:1809.04737 ( 2018 ). Yongkai Wu, Lu Zhang, and Xintao Wu. 2018. Fairness-aware classification: Criterion, convexity, and bounds. arXiv preprint arXiv:1809.04737 (2018)."},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/3382507.3418889"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACII52823.2021.9597439"},{"key":"e_1_3_2_1_66_1","volume-title":"Large batch optimization for deep learning: Training bert in 76 minutes. arXiv preprint arXiv:1904.00962","author":"You Yang","year":"2019","unstructured":"Yang You , Jing Li , Sashank Reddi , Jonathan Hseu , Sanjiv Kumar , Srinadh Bhojanapalli , Xiaodan Song , James Demmel , Kurt Keutzer , and Cho-Jui Hsieh . 2019. Large batch optimization for deep learning: Training bert in 76 minutes. arXiv preprint arXiv:1904.00962 ( 2019 ). Yang You, Jing Li, Sashank Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, and Cho-Jui Hsieh. 2019. Large batch optimization for deep learning: Training bert in 76 minutes. arXiv preprint arXiv:1904.00962 (2019)."},{"key":"e_1_3_2_1_67_1","volume-title":"Fairer Machine Learning Software on Multiple Sensitive Attributes With Data Preprocessing. arXiv preprint arXiv:2107.08310","author":"Yu Zhe","year":"2021","unstructured":"Zhe Yu , Joymallya Chakraborty , and Tim Menzies . 2021. Fairer Machine Learning Software on Multiple Sensitive Attributes With Data Preprocessing. arXiv preprint arXiv:2107.08310 ( 2021 ). Zhe Yu, Joymallya Chakraborty, and Tim Menzies. 2021. Fairer Machine Learning Software on Multiple Sensitive Attributes With Data Preprocessing. arXiv preprint arXiv:2107.08310 (2021)."},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1145\/3278721.3278779"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2015.2513401"}],"event":{"name":"MM '23: The 31st ACM International Conference on Multimedia","location":"Ottawa ON Canada","acronym":"MM '23","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 1st International Workshop on Multimodal and Responsible Affective Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3607865.3616175","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3607865.3616175","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:06Z","timestamp":1750178226000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3607865.3616175"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,29]]},"references-count":69,"alternative-id":["10.1145\/3607865.3616175","10.1145\/3607865"],"URL":"https:\/\/doi.org\/10.1145\/3607865.3616175","relation":{},"subject":[],"published":{"date-parts":[[2023,10,29]]},"assertion":[{"value":"2023-10-29","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}