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20122023
most citedDynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

311 citations · 1.1k across the 79 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CV2023★ 1 cited

TCOVIS: Temporally Consistent Online Video Instance Segmentation

Junlong Li, Bingyao Yu, Yongming Rao +2

In recent years, significant progress has been made in video instance segmentation (VIS), with many offline and online methods achieving state-of-the-art performance. While offline…

cs.CL2023★ 23 cited

Large Language Models Are Not Robust Multiple Choice Selectors

Chujie Zheng, Hao Zhou, Fandong Meng +2

Multiple choice questions (MCQs) serve as a common yet important task format in the evaluation of large language models (LLMs). This work shows that modern LLMs are vulnerable to o…

physics.app-ph2023★ 3 cited

Initial demonstration of AlGaAs-GaAsP-beta-Ga2O3 n-p-n double heterojunctions

Jie Zhou, Ashok Dheenan, Jiarui Gong +13

Beta phase gallium oxides, an ultrawide-bandgap semiconductor, has great potential for future power and RF electronics applications but faces challenges in bipolar device applicati…

physics.app-ph2023

Monocrystalline Si/-GaO p-n heterojunction diodes fabricated via grafting

Jiarui Gong, Donghyeok Kim, Hokyung Jang +19

The -GaO has exceptional electronic properties with vast potential in power and RF electronics. Despite the excellent demonstrations of high-performance unipolar devices…

math.NA2023

A convergence analysis of a structure-preserving gradient flow method for the all-electron Kohn-Sham model

Yedan Shen, Ting Wang, Jie Zhou +1

In [Dai et al, Multi. Model. Simul., 2020], a structure-preserving gradient flow method was proposed for the ground state calculation in Kohn-Sham density functional theory, based…

cs.CL2023★ 11 cited

Transformer-Patcher: One Mistake worth One Neuron

Zeyu Huang, Yikang Shen, Xiaofeng Zhang +3

Large Transformer-based Pretrained Language Models (PLMs) dominate almost all Natural Language Processing (NLP) tasks. Nevertheless, they still make mistakes from time to time. For…