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TyDiP: A Dataset for Politeness Classification in Nine Typologically
  Diverse Languages

TyDiP: A Dataset for Politeness Classification in Nine Typologically Diverse Languages

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
29 November 2022
A. Srinivasan
Eunsol Choi
ArXiv (abs)PDFHTML

Papers citing "TyDiP: A Dataset for Politeness Classification in Nine Typologically Diverse Languages"

14 / 14 papers shown
Title
Does AI Coaching Prepare us for Workplace Negotiations?
Does AI Coaching Prepare us for Workplace Negotiations?
Veda Duddu
Jash Rajesh Parekh
Andy Mao
Hanyi Min
Ziang Xiao
V. D. Swain
Koustuv Saha
81
0
0
26 Sep 2025
Multi-Agent Retrieval-Augmented Framework for Evidence-Based Counterspeech Against Health Misinformation
Multi-Agent Retrieval-Augmented Framework for Evidence-Based Counterspeech Against Health Misinformation
Anirban Saha Anik
Xiaoying Song
Elliott Wang
Bryan Wang
Bengisu Yarimbas
Lingzi Hong
RALM
182
1
0
09 Jul 2025
Does the Appearance of Autonomous Conversational Robots Affect User Spoken Behaviors in Real-World Conference Interactions?
Does the Appearance of Autonomous Conversational Robots Affect User Spoken Behaviors in Real-World Conference Interactions?
Zi Haur Pang
Yahui Fu
Divesh Lala
Mikey Elmers
K. Inoue
Tatsuya Kawahara
198
1
0
17 Mar 2025
"My life is miserable, have to sign 500 autographs everyday": Exposing Humblebragging, the Brags in Disguise
"My life is miserable, have to sign 500 autographs everyday": Exposing Humblebragging, the Brags in DisguiseAnnual Meeting of the Association for Computational Linguistics (ACL), 2024
Sharath Naganna
Saprativa Bhattacharjee
Biplab Banerjee
Pushpak Bhattacharyya
270
0
0
28 Dec 2024
Real or Robotic? Assessing Whether LLMs Accurately Simulate Qualities of
  Human Responses in Dialogue
Real or Robotic? Assessing Whether LLMs Accurately Simulate Qualities of Human Responses in Dialogue
Jonathan Ivey
Shivani Kumar
Jiayu Liu
Hua Shen
Sushrita Rakshit
...
Dustin Wright
Abraham Israeli
Anders Giovanni Møller
Lechen Zhang
David Jurgens
205
10
0
12 Sep 2024
Computational Politeness in Natural Language Processing: A Survey
Computational Politeness in Natural Language Processing: A Survey
Priyanshu Priya
Mauajama Firdaus
Asif Ekbal
173
17
0
28 Jun 2024
Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art
Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art
Chen Cecilia Liu
Iryna Gurevych
Anna Korhonen
446
14
0
06 Jun 2024
Revealing Trends in Datasets from the 2022 ACL and EMNLP Conferences
Revealing Trends in Datasets from the 2022 ACL and EMNLP Conferences
Jesse Atuhurra
Hidetaka Kamigaito
275
0
0
31 Mar 2024
What is "Typological Diversity" in NLP?
What is "Typological Diversity" in NLP?
Esther Ploeger
Wessel Poelman
Miryam de Lhoneux
Johannes Bjerva
329
4
0
06 Feb 2024
Multilingual estimation of political-party positioning: From label
  aggregation to long-input Transformers
Multilingual estimation of political-party positioning: From label aggregation to long-input TransformersConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Dmitry Nikolaev
Tanise Ceron
Sebastian Padó
161
2
0
19 Oct 2023
Comparing Styles across Languages: A Cross-Cultural Exploration of Politeness
Comparing Styles across Languages: A Cross-Cultural Exploration of PolitenessConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Shreya Havaldar
Matthew Pressimone
Eric Wong
Lyle Ungar
364
2
0
11 Oct 2023
Politeness Stereotypes and Attack Vectors: Gender Stereotypes in
  Japanese and Korean Language Models
Politeness Stereotypes and Attack Vectors: Gender Stereotypes in Japanese and Korean Language Models
Victor Steinborn
Antonis Maronikolakis
Hinrich Schütze
148
0
0
16 Jun 2023
When Do Annotator Demographics Matter? Measuring the Influence of
  Annotator Demographics with the POPQUORN Dataset
When Do Annotator Demographics Matter? Measuring the Influence of Annotator Demographics with the POPQUORN DatasetLaw (LAW), 2023
Jiaxin Pei
David Jurgens
202
52
0
12 Jun 2023
TyDi QA: A Benchmark for Information-Seeking Question Answering in
  Typologically Diverse Languages
TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse LanguagesTransactions of the Association for Computational Linguistics (TACL), 2020
J. Clark
Eunsol Choi
Michael Collins
Dan Garrette
Tom Kwiatkowski
Vitaly Nikolaev
J. Palomaki
464
683
0
10 Mar 2020
1