Yu-Yin Hsu

VLDB 2026 Research / reviewers in the wild / expert

dblp:157/2177 · DBLP profile ↗

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16ranked-venue papers

3as first author

11since 2021 · last 2026

0000-0003-4087-4995ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 16 · 3 first-author · 11 since 2021Graphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Year	Publication	Venue	Position
2026	The MultiplEYE Text Corpus: Towards a Diverse and Ever-Expanding Multilingual Text Corpus Ramune Kaspere, Anna Bondar, Sergiu Nisioi, Maja Stegenwallner-Schütz, Hanne B. Søndergaard Knudsen, Ana Matic Skoric, Eva Pavlinusic Vilus, Dorota Klimek-Jankowska, Chiara Tschirner, Not Battesta Soliva, Deborah N. Jakobi, Cui Ding, Dima Abu Romi, Cengiz Acartürk, Matilda Agdler, Anton Marius Alexandru, Mohd Faizan Ansari, Annalisa Arcidiacono, Elizabete Ausma Velta Barisa, Ana Bautista, Lisa Beinborn, Yevgeni Berzak, Nedeljka Bjelanovic, Anna Isabelle Bothmann, Jan Brasser, Caterina Cacioli, Anila Çepani, Ilze Ceple, Adelina Çerpja, Dalí Chirino, Jan Chromý, Alessandro Corona Mendozza, Iria de-Dios-Flores, Nazik Dinçtopal Deniz, Ana Dosen, Kristian Elersic, Inmaculada Fajardo, Zigmunds Freibergs, Angelina Ganebnaya, Jessica Gomes, Annjo Klungervik Greenall, Alba Haveriku, Anamaria Hodivoianu, Yu-Yin Hsu, Amanda Isaksen, Andreia Janeiro, Kristine M. Jensen de López, Aleksandar Jevremovic, Vojislav Jovanovic, Hanna Kedzierska, Nik Kharlamov, Sara Kosutar, Nelda Kote, Vanja Kovic, Izabela Krejtz, Thyra Krosness, Oleksandra Kuvshynova, Eilam Lavy, Ella Lion, Marta Lockiewicz, Kaidi Lõo, Paula Luegi, Mircea Mihai Marin, Clara Martin, Svitlana Matvieieva, Diane C. Mézière, Xavier Mínguez-López, Valeriia Modina, Jurgita Motiejuniene, Marie-Luise Müller, Tolgonai Nasipbek kyzy, Jamal Abdul Nasir, Johanne Sofie Krog Nedergård, Aysegül Özkan, Patrizia Paggio, Marijan Palmovic, Maria Christina Panagiotopoulou, Alberto Parola, Helena Pérez, Klaudia Petersen, Anja Podlesek, Eva Pospísilová, Marta Praulina, Mikulás Preininger, Loredana Punga, Diego Rossini, Spela Rot, Habib Sani Yahaya, Irina A. Sekerina, Anne Gabija Skadina, Jordi Solé i Casals, Lonneke van der Plas, Saara M. Varjopuro, Spyridoula Varlokosta, João Veríssimo, Oskari Juhapekka Virtanen, Nemanja Vracar, Mila Dimitrova-Vulchanova, Ahmad Mustapha Wali, Peizheng Wu, Nilgün Yücel, Stefan Frank, Nora Hollenstein, Lena A. Jäger, Somayeh Bakhtiari	LREC	46
2026	The Sensorimotor Norms for the Chinese Classifiers Yimei Shao, Yu-Yin Hsu, Chu-Ren Huang	LREC	2
2025	Mapping Acoustic Cues to Pragmatic Functions: Perceptual Cue Weighting of Prosodic Focus in Mandarin Wenxi Fei, Yu-Yin Hsu	CogSci	2
2025	Not Every Metric is Equal: Cognitive Models for Predicting N400 and P600 Components During Reading Comprehension abstract In recent years, numerous studies have sought to understand the cognitive dynamics underlying language processing by modeling reading times and ERP amplitudes using computational metrics like surprisal. In the present paper, we examine the predictive power of surprisal, entropy, and a novel metric based on semantic similarity for N400 and P600. Our experiments, conducted with Mandarin Chinese materials, revealed three key findings: 1) expectancy plays a primary role for N400; 2) P600 also reflects the cognitive effort required to evaluate linguistic input semantically; and 3) during the time window of interest, information uncertainty influences the language processing the most. Our findings show how computational metrics that capture distinct cognitive dimensions can effectively address psycholinguistic questions. Lavinia Salicchi, Yu-Yin Hsu	COLING	2
2025	When focus shapes the flow: prosodic restructuring in Mandarin complex nominals Anqi Xu 0002, Yu-Yin Hsu	INTERSPEECH	2
2025	'But this one was so . . . male.' A Corpus-Based and LLM-Augmented Analysis of Language and Gender Bias in Barbie Wing Hei Lok, Yu-Yin Hsu	PACLIC	3
2025	Sensory and Affective Dimensions in Mandarin Monosyllabic Adjectives Yimei Shao, Yu-Yin Hsu, Chu-Ren Huang	PACLIC	2
2024	Emstremo: Adapting Emotional Support Response with Enhanced Emotion-Strategy Integrated Selection abstract To provide effective support, it is essential for a skilled supporter to emotionally resonate with the help-seeker’s current emotional state. In conversational interactions, this emotional alignment is further influenced by the comforting strategies employed by the supporter. Different strategies guide the interlocutors to align their emotions in nuanced patterns. However, the incorporation of strategy into emotional alignment in the context of emotional support agents remains underexplored. To address this limitation, we propose an improved emotional support agent called Emstremo. Emstremo aims to achieve strategic control of emotional alignment by perceiving and responding to the user’s emotions. Our system’s state-of-the-art performance emphasizes the importance of integrating emotions and strategies in modeling conversations that provide emotional support. Yu-Yin Hsu	LREC/COLING	3
2024	Comparing Static and Contextual Distributional Semantic Models on Intrinsic Tasks: An Evaluation on Mandarin Chinese Datasets abstract The field of Distributional Semantics has recently undergone important changes, with the contextual representations produced by Transformers taking the place of static word embeddings models. Noticeably, previous studies comparing the two types of vectors have only focused on the English language and a limited number of models. In our study, we present a comparative evaluation of static and contextualized distributional models for Mandarin Chinese, focusing on a range of intrinsic tasks. Our results reveal that static models remain stronger for some of the classical tasks that consider word meaning independent of context, while contextualized models excel in identifying semantic relations between word pairs and in the categorization of words into abstract semantic classes. A Pranav 0001, Yan Cong, Emmanuele Chersoni, Yu-Yin Hsu, Alessandro Lenci	LREC/COLING	4
2024	Be Helpful but Don't Talk too Much - Enhancing Helpfulness in Conversations through Relevance in Multi-Turn Emotional Support abstract For a conversation to help and support, speakers should maintain an "effect-effort" trade-off.As outlined in the gist of "Cognitive Relevance Principle", helpful speakers should optimize the "cognitive relevance" through maximizing the "cognitive effects" and minimizing the "processing effort" imposed on listeners.Although preference learning methods provide a boon for studies concerning "effect-optimization", none have delved into "effort-optimization" which is pivotal to the acquisition of "optimal relevance" for emotional support conversation agents.To address this gap, we integrate the "Cognitive Relevance Principle" into emotional support agents in the environment of multi-turn conversation.The results demonstrate a significant and robust improvement against the baseline systems with respect to response quality, human-likedness, and supportiveness.This study offers compelling evidence for the effectiveness of the "Relevance Principle" in generating human-like, helpful, and harmless emotional support conversations. Yu-Yin Hsu, Chu-Ren Huang	EMNLP	3
2024	Supervised Cross-Momentum Contrast: Aligning representations with prototypical examples to enhance financial sentiment analysis abstract Financial sentiment analysis plays a pivotal role in understanding market dynamics and investor sentiment. In this paper, we propose the Supervised Cross-Momentum Contrast (SuCroMoCo) framework, a novel approach for financial sentiment analysis. SuCroMoCo leverages supervised contrastive learning and cross-momentum contrast to align financial text representations with prototypical representations based on sentiment categories. This alignment greatly improves classification performance, addressing the limitations of pre-trained language models (PLMs) in fully grasping the intricate nature of financial text. Through extensive experiments, we demonstrate that SuCroMoCo outperforms existing PLMs-based approaches and Large Language Models (LLMs) on diverse benchmark datasets. The code and datasets can be found in https://github.com/PengBO-O/SuCroMoCo. Emmanuele Chersoni, Yu-Yin Hsu, Le Qiu, Chu-Ren Huang	Knowl. Based Syst.	3
2020	Predicting gender and age categories in English conversations using lexical, non-lexical, and turn-taking features Andreas Liesenfeld, Gábor Parti, Yu-Yin Hsu, Chu-Ren Huang	PACLIC	3
2019	Sentence Prosody and Wh-Indeterminates in Taiwan Mandarin abstract 202303 bcww Yu-Yin Hsu, Anqi Xu 0002	INTERSPEECH	1
2018	Prosodic Organization and Focus Realization in Taiwan Mandarin Yu-Yin Hsu, James Sneed German	PACLIC	1
2018	Whether and How Mandarin Sandhied Tone 3 and Underlying Tone 2 differ in Terms of Vowel Quality? Yu-Jung Lin, Yu-Yin Hsu	PACLIC	2
2017	Focus Acoustics in Mandarin Nominals abstract 2017-2018 > Academic research: refereed > Refereed conference paper Yu-Yin Hsu, Anqi Xu 0002	INTERSPEECH	1