no code implementations • 15 Nov 2024 • Minglu Zhao, Dehong Xu, Deqian Kong, Wen-Hao Zhang, Ying Nian Wu
We demonstrate the emergence of Gaussian-like tuning profiles and a 2D circle geometry in both versions of the model.
no code implementations • 4 Jun 2024 • Dehong Xu, Liang Qiu, Minseok Kim, Faisal Ladhak, Jaeyoung Do
Pre-trained large-scale language models (LLMs) excel at producing coherent articles, yet their outputs may be untruthful, toxic, or fail to align with user expectations.
no code implementations • 27 May 2024 • Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
As the agent moves, this vector rotates within a 2D manifold in the neural space, driven by a recurrent neural network.
no code implementations • 25 Apr 2024 • Minglu Zhao, Dehong Xu, Tao Gao
Attention is a cornerstone of human cognition that facilitates the efficient extraction of information in everyday life.
1 code implementation • 7 Feb 2024 • Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu
We introduce the Latent Plan Transformer (LPT), a novel model that leverages a latent variable to connect a Transformer-based trajectory generator and the final return.
no code implementations • 29 Oct 2023 • Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
As the agent moves, the vector is transformed by an RNN that takes the velocity of the agent as input.
1 code implementation • 1 Jun 2023 • Yan Xu, Deqian Kong, Dehong Xu, Ziwei Ji, Bo Pang, Pascale Fung, Ying Nian Wu
The capability to generate responses with diversity and faithfulness using factual knowledge is paramount for creating a human-like, trustworthy dialogue system.
1 code implementation • 6 Oct 2022 • Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
Recurrent neural networks have been proposed to explain the properties of the grid cells by updating the neural activity vector based on the velocity input of the animal.