Zobrazeno 1 - 10
of 476
pro vyhledávání: '"SUN Jingyuan"'
Publikováno v:
Taiyuan Ligong Daxue xuebao, Vol 55, Iss 5, Pp 850-856 (2024)
Purposes To investigate the influence of different tamping methods on the reinforcement effect of sand dynamic compaction, this research has been done from the perspective of soil stress distribution characteristics. Methods The dynamic compaction mo
Externí odkaz:
https://doaj.org/article/00410de8e5184518b53949c57ed68139
Through end-to-end training to predict the next token, LLMs have become valuable tools for various tasks. Enhancing their core training in language modeling can improve numerous downstream applications. A successful approach to enhance language model
Externí odkaz:
http://arxiv.org/abs/2410.12492
Argument structure learning~(ASL) entails predicting relations between arguments. Because it can structure a document to facilitate its understanding, it has been widely applied in many fields~(medical, commercial, and scientific domains). Despite it
Externí odkaz:
http://arxiv.org/abs/2405.01216
Decoding continuous language from brain activity is a formidable yet promising field of research. It is particularly significant for aiding people with speech disabilities to communicate through brain signals. This field addresses the complex task of
Externí odkaz:
http://arxiv.org/abs/2403.17516
Autor:
Wang, Shaonan, Sun, Jingyuan, Zhang, Yunhao, Lin, Nan, Moens, Marie-Francine, Zong, Chengqing
Despite differing from the human language processing mechanism in implementation and algorithms, current language models demonstrate remarkable human-like or surpassing language capabilities. Should computational language models be employed in studyi
Externí odkaz:
http://arxiv.org/abs/2403.13368
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. While recent advancements have achieved success in rec
Externí odkaz:
http://arxiv.org/abs/2402.01590
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
Externí odkaz:
http://arxiv.org/abs/2310.04460
Autor:
Sun, Jingyuan, Moens, Marie-Francine
To decipher the algorithm underlying the human brain's language representation, previous work probed brain responses to language input with pre-trained artificial neural network (ANN) models fine-tuned on NLU tasks. However, full fine-tuning generall
Externí odkaz:
http://arxiv.org/abs/2310.01854
Decoding Realistic Images from Brain Activity with Contrastive Self-supervision and Latent Diffusion
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. Although deep generative models have been employed fo
Externí odkaz:
http://arxiv.org/abs/2310.00318
Autor:
Sun, Jingyuan, Li, Mingxiao, Chen, Zijiao, Zhang, Yunhao, Wang, Shaonan, Moens, Marie-Francine
Decoding visual stimuli from neural responses recorded by functional Magnetic Resonance Imaging (fMRI) presents an intriguing intersection between cognitive neuroscience and machine learning, promising advancements in understanding human visual perce
Externí odkaz:
http://arxiv.org/abs/2305.17214