no code implementations • 6 Jun 2023 • Violetta Rostobaya, Yue Guan, James Berneburg, Michael Dorothy, Daigo Shishika
This paper studies the idea of ``deception by motion'' through a two-player dynamic game played between a Mover who must retrieve resources at a goal location, and an Eater who can consume resources at two candidate goals.
1 code implementation • 22 Mar 2023 • Yue Guan, Mohammad Afshari, Panagiotis Tsiotras
This work studies the behaviors of two large-population teams competing in a discrete environment.
no code implementations • 27 Sep 2022 • Yue Guan, Longxu Pan, Daigo Shishika, Panagiotis Tsiotras
In this work, we extend the convex bodies chasing problem (CBC) to an adversarial setting, where an agent (the Player) is tasked with chasing a sequence of convex bodies generated adversarially by another agent (the Opponent).
1 code implementation • ACL 2022 • Yue Guan, Zhengyi Li, Jingwen Leng, Zhouhan Lin, Minyi Guo
To address the above limitations, we propose the Transkimmer architecture, which learns to identify hidden state tokens that are not required by each layer.
no code implementations • 18 Dec 2021 • Daigo Shishika, Yue Guan, Michael Dorothy, Vijay Kumar
The game terminates with the attacker's win if any location has more attacker robots than defender robots at any time.
1 code implementation • 16 Dec 2021 • Yue Guan, Zhengyi Li, Jingwen Leng, Zhouhan Lin, Minyi Guo, Yuhao Zhu
We further prune the hidden states corresponding to the unnecessary positions early in lower layers, achieving significant inference-time speedup.
no code implementations • 22 Sep 2021 • Tianfang Zhu, Yue Guan, Anan Li
We use both the supervised and the self-supervised models for the denoising and introduce a new cost term for the joint denoising and the segmentation setup.
no code implementations • 15 Sep 2021 • Tianfang Zhu, Yue Guan, Anan Li
This paper proposes a point cloud augmentation approach, PointManifoldCut(PMC), which replaces the neural network embedded points, rather than the Euclidean space coordinates.
no code implementations • 1 Jan 2021 • Yue Guan, Jingwen Leng, Yuhao Zhu, Minyi Guo
Following this idea, we proposed Block Skim Transformer (BST) to improve and accelerate the processing of transformer QA models.
no code implementations • COLING 2020 • Yue Guan, Jingwen Leng, Chao Li, Quan Chen, Minyi Guo
Recent research on the multi-head attention mechanism, especially that in pre-trained models such as BERT, has shown us heuristics and clues in analyzing various aspects of the mechanism.
no code implementations • 2 Nov 2020 • Yue Guan, Jingwen Leng, Chao Li, Quan Chen, Minyi Guo
Recent research on the multi-head attention mechanism, especially that in pre-trained models such as BERT, has shown us heuristics and clues in analyzing various aspects of the mechanism.
no code implementations • 1 Sep 2020 • Yue Guan, Qifan Zhang, Panagiotis Tsiotras
We explore the use of policy approximations to reduce the computational cost of learning Nash equilibria in zero-sum stochastic games.
1 code implementation • 29 Aug 2020 • Cong Guo, Bo Yang Hsueh, Jingwen Leng, Yuxian Qiu, Yue Guan, Zehuan Wang, Xiaoying Jia, Xipeng Li, Minyi Guo, Yuhao Zhu
Network pruning can reduce the high computation cost of deep neural network (DNN) models.
1 code implementation • ICCV 2019 • Youjiang Xu, Jiaqi Duan, Zhanghui Kuang, Xiaoyu Yue, Hongbin Sun, Yue Guan, Wayne Zhang
Large geometry (e. g., orientation) variances are the key challenges in the scene text detection.
Ranked #10 on Scene Text Detection on ICDAR 2017 MLT