Dota - Tianai Dong

Hi! I am a second-year PhD student, affiliated with Multimodal Language Department at the Max Planck Institute for Psycholinguistics, and Predictive Brain Lab at the Donders Institute (Centre for Cognitive Neuroimaging). I am co-advised by Floris de Lange , Lea-Maria Schmitt , Stefan Frank, and Paula Rubio-Fernández . I also work closely with Mariya Toneva at the Max Planck Institute for Software Systems. I am funded by an IMPRS fellowship.

My research interests lie at the intersection of machine learning, and cognitive neuroscience (with a focus on language). I am particularly interested in understanding the computational and cognitive principles that underlie human multimodal percept. I mainly use computational methods to study these questions, in conjunction with data and theories from neuroscience, linguistics, and psychology.

If you want to discuss any academia-related topics, please feel free to reach out to me :)

Email // Google Scholar // Twitter

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Multimodal Video Transformers Partially Align with Multimodal Grounding and Compositionality in the Brain
Dota Tianai Dong, Mariya Toneva
ICLR-MRL, 2023; CCN, 2023; Preprint, 2024

We propose to probe a pre-trained multimodal video transformer model, guided by insights from neuroscientific evidence on multimodal information processing in the human brain.

Discogem: A crowdsourced corpus of genre-mixed implicit discourse relations
Merel Scholman Dota Tianai Dong, Frances Yung, Vera Demberg
LREC, 2022;

We present DiscoGeM, a crowdsourced corpus of 6,505 implicit discourse relations from three genres: political speech, literature, and encyclopedic text.

Comparison of methods for explicit discourse connective identification across various domains
Merel Scholman Dota Tianai Dong, Frances Yung, Vera Demberg
CODI, 2021;

We assess the performance on explicit connective identification of four parse methods (PDTB e2e, Lin et al., 2014; the winner of CONLL2015, Wang and Lan, 2015; DisSent, Nie et al., 2019; and Discopy, Knaebel and Stede, 2020), along with a simple heuristic.

Visually grounded follow-up questions: A dataset of spatial questions which require dialogue history
Dota Tianai Dong, Alberto Testoni, Luciana Benotti, Raffaella Bernardi
Splurobonlp, 2021;

We define and evaluate a methodology for extracting history-dependent spatial questions from visual dialogues.

Analyses of Multiple Discourse Relations within a Chinese Sentence
Dota Tianai Dong, Bonnie Webber, Jennifer Spenader
Bachelor Thesis

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