category

Publications

2021

P. P. Liang, Y. Lyu, X. Fan, Z. Wu, Y. Cheng, J. Wu, L. Chen, P. Wu, M. Lee, Y. Zhu, R. Salakhutdinov, L.-P. Morency. MultiBench: Multiscale Benchmarks for Multimodal Representation Learning. NeurIPS 2021 Datasets and Benchmarks Track

Links: PDF Demo & Code

Y.-H. H. Tsai*, M. Q. Ma*, M. Yang, H. Zhao, L.-P. Morency, R. Salakhutdinov. Self-supervised Representation Learning with Relative Predictive Coding. International Conference on Learning Representations (ICLR) 2021.

Links: PDF

Y.-H. H. Tsai, Y. Wu, R. Salakhutdinov, L.-P. Morency. Self-supervised Learning from a Multi-view Perspective. International Conference on Learning Representations (ICLR) 2021

Links: PDF Demo & Code

P. Wu, P. P. Liang, J. Shi, R. Salakhutdinov, S. Watanabe, L.-P. Morency. Understanding the Tradeoffs in Client-side Privacy for Downstream Speech Tasks. Asia Pacific Signal and Information Processing Association Annual Summit and Conference 2021

Links: PDF Demo & Code

P. P. Liang, C. Wu, L.-P. Morency, R. Salakhutdinov. Towards Understanding and Mitigating Social Biases in Language Models. ICML 2021

Links: PDF Demo & Code

P. P. Liang*, T. Liu*, A. Cai, M. Muszynski, R. Ishii, N. Allen, R. Auerbach, D. Brent, R. Salakhutdinov, L.-P. Morency. Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data. ACL 2021

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T. Wörtwein, L. B. Sheeber, N. Allen, J. F. Cohn, L.-P. Morency. Human-Guided Modality Informativeness for Affective States. In Proceedings of the 2021 International Conference on Multimodal Interaction (ICMI ’21).

Links: PDF

2020

V. Cirik, T. Berg-Kirkpatrick, L.-P. Morency. Refer360°: A Referring Expression Recognition Dataset in 360° Images, ACL 2020

Links: PDF Demo & Code Videos

V. Lin*, J. M. Girard*, M. A. Sayette, L.-P. Morency (2020). Toward Multimodal Modeling of Emotional Expressiveness. In Proceedings of the 2020 International Conference on Multimodal Interaction (ICMI) (pp. 548-557).

Links: PDF Publications Demo & Code

T. Wörtwein and L-P Morency. Simple and Effective Approaches for Uncertainty Prediction in Facial Action Unit Intensity Regression. FG 2020

Links: PDF Demo & Code