1 code implementation • 2 May 2024 • Wei Sun, Mingxiao Li, Jingyuan Sun, Jesse Davis, Marie-Francine Moens
Argument structure learning~(ASL) entails predicting relations between arguments.
no code implementations • 26 Mar 2024 • Xinpei Zhao, Jingyuan Sun, Shaonan Wang, Jing Ye, Xiaohan Zhang, Chengqing Zong
In contrast, we propose a simple yet effective method that guides text reconstruction by directly comparing them with the predicted text embeddings mapped from brain activities.
no code implementations • 20 Mar 2024 • Shaonan Wang, Jingyuan Sun, Yunhao Zhang, Nan Lin, Marie-Francine Moens, Chengqing Zong
Despite differing from the human language processing mechanism in implementation and algorithms, current language models demonstrate remarkable human-like or surpassing language capabilities.
no code implementations • 2 Feb 2024 • Jingyuan Sun, Mingxiao Li, Zijiao Chen, Marie-Francine Moens
In the pursuit to understand the intricacies of human brain's visual processing, reconstructing dynamic visual experiences from brain activities emerges as a challenging yet fascinating endeavor.
no code implementations • 5 Oct 2023 • Jingyuan Sun, Xiaohan Zhang, Marie-Francine Moens
To understand the algorithm that supports the human brain's language representation, previous research has attempted to predict neural responses to linguistic stimuli using embeddings generated by artificial neural networks (ANNs), a process known as neural encoding.
no code implementations • 3 Oct 2023 • Jingyuan Sun, Marie-Francine Moens
If so, what kind of NLU task leads a pre-trained model to better decode the information represented in the human brain?
no code implementations • 30 Sep 2023 • Jingyuan Sun, Mingxiao Li, Marie-Francine Moens
Reconstructing visual stimuli from human brain activities provides a promising opportunity to advance our understanding of the brain's visual system and its connection with computer vision models.
1 code implementation • NeurIPS 2023 • Jingyuan Sun, Mingxiao Li, Zijiao Chen, Yunhao Zhang, Shaonan Wang, Marie-Francine Moens
The second phase tunes the feature learner to attend to neural activation patterns most informative for visual reconstruction with guidance from an image auto-encoder.
Ranked #1 on Brain Visual Reconstruction from fMRI on GOD
no code implementations • COLING 2020 • Jingyuan Sun, Shaonan Wang, Jiajun Zhang, Chengqing Zong
The framework is based on language models and can be smoothly built with different language model architectures.
no code implementations • EMNLP 2018 • Jingyuan Sun, Shaonan Wang, Cheng-qing Zong
Distributional semantic models (DSMs) generally require sufficient examples for a word to learn a high quality representation.