Sense Embeddings are also Biased–Evaluating Social Biases in Static and Contextualised Sense Embeddings

Kavli Affiliate: Yi Zhou | First 5 Authors: Yi Zhou, Masahiro Kaneko, Danushka Bollegala, , | Summary: Sense embedding learning methods learn different embeddings for the different senses of an ambiguous word. One sense of an ambiguous word might be socially biased while its other senses remain unbiased. In comparison to the numerous prior work […]


Continue.. Sense Embeddings are also Biased–Evaluating Social Biases in Static and Contextualised Sense Embeddings

Possible chiral spin liquid state in the $S=1/2$ kagome Heisenberg model

Kavli Affiliate: Yi Zhou | First 5 Authors: Rong-Yang Sun, Hui-Ke Jin, Hong-Hao Tu, Yi Zhou, | Summary: The nature of the ground state for the $S = 1/2$ kagome Heisenberg antiferromagnet (KHAF) has been elusive. We revisit this challenging problem and provide numerical evidence that its ground state might be a chiral spin liquid. […]


Continue.. Possible chiral spin liquid state in the $S=1/2$ kagome Heisenberg model

GaitStrip: Gait Recognition via Effective Strip-based Feature Representations and Multi-Level Framework

Kavli Affiliate: Zheng Zhu | First 5 Authors: Ming Wang, Beibei Lin, Xianda Guo, Lincheng Li, Zheng Zhu | Summary: Many gait recognition methods first partition the human gait into N-parts and then combine them to establish part-based feature representations. Their gait recognition performance is often affected by partitioning strategies, which are empirically chosen in […]


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Towards performant and reliable undersampled MR reconstruction via diffusion model sampling

Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Pengfei Guo, S. Kevin Zhou, Vishal Patel, Rama Chellappa | Summary: Magnetic Resonance (MR) image reconstruction from under-sampled acquisition promises faster scanning time. To this end, current State-of-The-Art (SoTA) approaches leverage deep neural networks and supervised training to learn a recovery model. While these approaches […]


Continue.. Towards performant and reliable undersampled MR reconstruction via diffusion model sampling

Extended Load Flexibility of Industrial P2H Plants: A Process Constraint-Aware Scheduling Approach

Kavli Affiliate: Yi Zhou | First 5 Authors: Yiwei Qiu, Buxiang Zhou, Tianlei Zang, Yi Zhou, Ruomei Qi | Summary: The operational flexibility of industrial power-to-hydrogen (P2H) plants enables admittance of volatile renewable power and provides auxiliary regulatory services for the power grid. Aiming to extend the flexibility of the P2H plant further, this work […]


Continue.. Extended Load Flexibility of Industrial P2H Plants: A Process Constraint-Aware Scheduling Approach

ACVNet: Attention Concatenation Volume for Accurate and Efficient Stereo Matching

Kavli Affiliate: Cheng Peng | First 5 Authors: Gangwei Xu, Junda Cheng, Peng Guo, Xin Yang, | Summary: Stereo matching is a fundamental building block for many vision and robotics applications. An informative and concise cost volume representation is vital for stereo matching of high accuracy and efficiency. In this paper, we present a novel […]


Continue.. ACVNet: Attention Concatenation Volume for Accurate and Efficient Stereo Matching

ACVNet: Attention Concatenation Volume for Accurate and Efficient Stereo Matching

Kavli Affiliate: Cheng Peng | First 5 Authors: Gangwei Xu, Junda Cheng, Peng Guo, Xin Yang, | Summary: Stereo matching is a fundamental building block for many vision and robotics applications. An informative and concise cost volume representation is vital for stereo matching of high accuracy and efficiency. In this paper, we present a novel […]


Continue.. ACVNet: Attention Concatenation Volume for Accurate and Efficient Stereo Matching

Attention Concatenation Volume for Accurate and Efficient Stereo Matching

Kavli Affiliate: Cheng Peng | First 5 Authors: Gangwei Xu, Junda Cheng, Peng Guo, Xin Yang, | Summary: Stereo matching is a fundamental building block for many vision and robotics applications. An informative and concise cost volume representation is vital for stereo matching of high accuracy and efficiency. In this paper, we present a novel […]


Continue.. Attention Concatenation Volume for Accurate and Efficient Stereo Matching

CAFE: Learning to Condense Dataset by Aligning Features

Kavli Affiliate: Zheng Zhu | First 5 Authors: Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Shuo Yang | Summary: Dataset condensation aims at reducing the network training effort through condensing a cumbersome training set into a compact synthetic one. State-of-the-art approaches largely rely on learning the synthetic data by matching the gradients between the […]


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Pomeranchuk Effect and Tunable Quantum Phase Transitions in 3L-MoTe2/WSe2

Kavli Affiliate: Zheng Zhu | First 5 Authors: Mingjie Zhang, Xuan Zhao, Kenji Watanabe, Takashi Taniguchi, Zheng Zhu | Summary: Many sought-after exotic states of matter are known to emerge close to quantum phase transitions, such as quantum spin liquids (QSL) and unconventional superconductivity. It is thus desirable to experimentally explore systems that can be […]


Continue.. Pomeranchuk Effect and Tunable Quantum Phase Transitions in 3L-MoTe2/WSe2