Maria Teleki
Orcid: 0009-0006-7015-4015
According to our database1,
Maria Teleki authored at least 20 papers
between 2023 and 2026.
Collaborative distances:
Collaborative distances:
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Bibliography
2026
Beyond Single Ground Truth: Reference Monism as Epistemic Injustice in ASR Evaluation.
CoRR, May, 2026
CoRR, March, 2026
"Walk a Mile in My Voice": Voice Conversion Shapes Trust, Attribution, and Empathy in Human-AI Speech Interactions.
Proceedings of the Companion Proceedings of the 31st International Conference on Intelligent User Interfaces, 2026
Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026
Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems, 2026
From Seeing it to Experiencing it: Interactive Evaluation of Intersectional Voice Bias in Human-AI Speech Interaction.
Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems, 2026
PromptHelper: A Prompt Recommender System for Encouraging Creativity in AI Chatbot Interactions.
Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems, 2026
2025
CoRR, September, 2025
I want a horror - comedy - movie: Slips-of-the-Tongue Impact Conversational Recommender System Performance.
Proceedings of the 26th Annual Conference of the International Speech Communication Association, 2025
Proceedings of the Nineteenth International AAAI Conference on Web and Social Media, 2025
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
2024
Proceedings of the 25th Annual Conference of the International Speech Communication Association, 2024
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024
2023
Co$^2$PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning.
CoRR, 2023
Co²PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023