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Dr Carla Perez Almendros
(hi/nhw)
- Ar gael fel goruchwyliwr ôl-raddedig
Timau a rolau for Carla Perez Almendros
Staff academaidd ac ymchwil
Darlithydd
Trosolwg
Rwy'n ddarlithydd ac ymchwilydd llawn amser yn yr Ysgol Cyfrifiadureg a Gwybodeg, sy'n arbenigo mewn Prosesu Iaith Naturiol (NLP). Cyn fy ngyrfa yn NLP astudiais Cysylltiadau Cyhoeddus a Chyfrifoldeb Cymdeithasol a gweithiais am 10+ mlynedd mewn cyfathrebu, yn enwedig yn y sector dielw. Rwy'n Gymrawd o'r Academi Addysg Uwch (FHEA).
Roedd fy PhD yn canolbwyntio ar ganfod Patronizing a Condescending Langauge yn awtomatig tuag at gymunedau agored i niwed. Ers hynny, rwyf wedi arbenigo mewn rhagfarn (cynnil), microymosodiadau a chanfod gwahaniaethu trwy ac o fewn modelau NLP.
Fy mhrif bynciau ymchwil yw cymwysiadau ar gyfer Prosesu Iaith Naturiol (NLP), NLP ar gyfer effaith gymdeithasol ac AI Cyfrifol. Agored i oruchwyliaeth PhD.
Cyhoeddiad
2026
- Antypas, D. et al. 2026. Causal effects of trigger words in social media discussions: a large-scale case study about UK politics on Reddit. Presented at: WebSci '26: 18th ACM Web Science Conference Braunschweig, Germany 26-29 May 2026. Published in: Balke, W. et al., Proceedings of the 18th ACM Web Science Conference. New York, NY, US: ACM. , pp.359-369. (10.1145/3795766.3799750)
2024
- Myung, J. et al., 2024. BLEND: A benchmark for LLMs on everyday knowledge in diverse cultures and languages. Presented at: 38th Conference on Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and Benchmarks Vancouver, BC, Canada 9-15 December 2024. Published in: Globerson, A. et al., NeurIPS Proceedings: Advances in Neural Information Processing Systems. Vol. 37.Curran Associates, Inc.. , pp.78104-78146.
- Antypas, D. et al. 2024. Sensitive content classification in social media: A holistic resource and evaluation. [Online].arXiv. (10.48550/arXiv.2411.19832)Available at: https://doi.org/10.48550/arXiv.2411.19832.
- Antypas, D. et al. 2024. Words as trigger points in social media discussions. [Online].arXiv. (10.48550/arXiv.2405.10213)Available at: https://doi.org/10.48550/arXiv.2405.10213.
- Perez Almendros, C. and Camacho Collados, J. 2024. Do Large Language Models understand mansplaining? Well, actually.... Presented at: LREC-COLING 2024 - The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation Torino, Itay 20-25 May 2024. Published in: Calzolari, N. et al., Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). ELRA and ICCL. , pp.5235-5246.
2023
- Perez Almendros, C. 2023. Automatic detection of patronizing and condescending language towards vulnerable communities. PhD Thesis , Cardiff University.
2022
- Perez Almendros, C. and Schockaert, S. 2022. Identifying condescending language: a tale of two distinct phenomena?. Presented at: Second Workshop on NLP for Positive Impact (NLP4PI) Abu Dhabi, United Arab Emirates (Hybrid) 7 December 2022. Published in: Biester, L. et al., Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI). Association for Computational Linguistics. , pp.130–141. (10.18653/v1/2022.nlp4pi-1.15)
- Perez-Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2022. SemEval-2022 task 4: patronizing and condescending language detection. Presented at: 16th International Workshop on Semantic Evaluation (SemEval-2022) Seattle, United States July 2022. Published in: Emerson, G. et al., Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022). Association for Computational Linguistics. , pp.298–307. (10.18653/v1/2022.semeval-1.38)
- Perez Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2022. Pre-training language models for identifying patronizing and condescending language: an analysis. Presented at: LREC 2022 Marseille; France 20-25 June 2022. Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association. , pp.3902-3911.
2020
- Perez Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2020. Don’t patronize me! An annotated dataset with patronizing and condescending language towards vulnerable communities. Presented at: 28th International Conference on Computational Linguistics (COLING) Barcelona, Spain 13-18 December 2020. Published in: Scott, D. , Bel, N. and Zong, C. eds. Proceedings of the 28th International Conference on Computational Linguistics. International Committee on Computational Linguistics. , pp.5891–5902. (10.18653/v1/2020.coling-main.518)
2019
- Torres Valdés, R. M. , Santa Soriano, A. and Pérez Almendros, C. 2019. The transference of theoretical models to productive transdisciplinary intersections in public relations management: Eight case studies addressing wicked problems. Public Relations Review 45 (5) 101799. (10.1016/j.pubrev.2019.101799)
- Perez Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2019. Cardiff University at SemEval-2019 Task 4: Linguistic features for hyperpartisan news detection. Presented at: SemEval-2019: International Workshop on Semantic Evaluation Minneapolis, Minnesota, USA 6-7 June 2019. Published in: May, J. et al., Proceedings of the 13th International Workshop on Semantic Evaluation. Association for Computational Linguistics. , pp.929-933. (10.18653/v1/S19-2158)
Cynadleddau
- Antypas, D. et al. 2026. Causal effects of trigger words in social media discussions: a large-scale case study about UK politics on Reddit. Presented at: WebSci '26: 18th ACM Web Science Conference Braunschweig, Germany 26-29 May 2026. Published in: Balke, W. et al., Proceedings of the 18th ACM Web Science Conference. New York, NY, US: ACM. , pp.359-369. (10.1145/3795766.3799750)
- Myung, J. et al., 2024. BLEND: A benchmark for LLMs on everyday knowledge in diverse cultures and languages. Presented at: 38th Conference on Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and Benchmarks Vancouver, BC, Canada 9-15 December 2024. Published in: Globerson, A. et al., NeurIPS Proceedings: Advances in Neural Information Processing Systems. Vol. 37.Curran Associates, Inc.. , pp.78104-78146.
- Perez Almendros, C. and Camacho Collados, J. 2024. Do Large Language Models understand mansplaining? Well, actually.... Presented at: LREC-COLING 2024 - The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation Torino, Itay 20-25 May 2024. Published in: Calzolari, N. et al., Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). ELRA and ICCL. , pp.5235-5246.
- Perez Almendros, C. and Schockaert, S. 2022. Identifying condescending language: a tale of two distinct phenomena?. Presented at: Second Workshop on NLP for Positive Impact (NLP4PI) Abu Dhabi, United Arab Emirates (Hybrid) 7 December 2022. Published in: Biester, L. et al., Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI). Association for Computational Linguistics. , pp.130–141. (10.18653/v1/2022.nlp4pi-1.15)
- Perez-Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2022. SemEval-2022 task 4: patronizing and condescending language detection. Presented at: 16th International Workshop on Semantic Evaluation (SemEval-2022) Seattle, United States July 2022. Published in: Emerson, G. et al., Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022). Association for Computational Linguistics. , pp.298–307. (10.18653/v1/2022.semeval-1.38)
- Perez Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2022. Pre-training language models for identifying patronizing and condescending language: an analysis. Presented at: LREC 2022 Marseille; France 20-25 June 2022. Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association. , pp.3902-3911.
- Perez Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2020. Don’t patronize me! An annotated dataset with patronizing and condescending language towards vulnerable communities. Presented at: 28th International Conference on Computational Linguistics (COLING) Barcelona, Spain 13-18 December 2020. Published in: Scott, D. , Bel, N. and Zong, C. eds. Proceedings of the 28th International Conference on Computational Linguistics. International Committee on Computational Linguistics. , pp.5891–5902. (10.18653/v1/2020.coling-main.518)
- Perez Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2019. Cardiff University at SemEval-2019 Task 4: Linguistic features for hyperpartisan news detection. Presented at: SemEval-2019: International Workshop on Semantic Evaluation Minneapolis, Minnesota, USA 6-7 June 2019. Published in: May, J. et al., Proceedings of the 13th International Workshop on Semantic Evaluation. Association for Computational Linguistics. , pp.929-933. (10.18653/v1/S19-2158)
Erthyglau
- Torres Valdés, R. M. , Santa Soriano, A. and Pérez Almendros, C. 2019. The transference of theoretical models to productive transdisciplinary intersections in public relations management: Eight case studies addressing wicked problems. Public Relations Review 45 (5) 101799. (10.1016/j.pubrev.2019.101799)
Gosodiad
- Perez Almendros, C. 2023. Automatic detection of patronizing and condescending language towards vulnerable communities. PhD Thesis , Cardiff University.
Gwefannau
- Antypas, D. et al. 2024. Sensitive content classification in social media: A holistic resource and evaluation. [Online].arXiv. (10.48550/arXiv.2411.19832)Available at: https://doi.org/10.48550/arXiv.2411.19832.
- Antypas, D. et al. 2024. Words as trigger points in social media discussions. [Online].arXiv. (10.48550/arXiv.2405.10213)Available at: https://doi.org/10.48550/arXiv.2405.10213.
Addysgu
Ieithyddiaeth Gyfrifiadurol
Prosesu Iaith Naturiol
Python
Rhagfarn mewn NLP
AI Cyfrifol
Meysydd goruchwyliaeth
- AI Cyfrifol
- Rhagfarn mewn NLP
- Mecanweithiau diogelwch
Dwy swydd agored ar hyn o bryd:
AI Diogel mewn Argyfwng: Datblygu Mecanweithiau Rheoli ar gyfer Ymatebion LLM i Gynnwys Hunanladdol a CYmateb risis
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Themâu ymchwil
Arbenigeddau
- Prosesu iaith naturiol
- Moeseg AI
- Modelau Iaith
- Rhagfarn yn NLP
- AI cyfrifol