Search Results for author: Yihao Wang

Found 8 papers, 2 papers with code

LLsM: Generative Linguistic Steganography with Large Language Model

no code implementations28 Jan 2024 Yihao Wang, Ruiqi Song, Ru Zhang, Jianyi Liu, Lingxiao Li

However, the controllability of the stego generated by existing schemes is poor, and the stego is difficult to contain specific discourse characteristics such as style.

Language Modelling Large Language Model +2

Propagate And Calibrate: Real-time Passive Non-line-of-sight Tracking

no code implementations CVPR 2023 Yihao Wang, Zhigang Wang, Bin Zhao, Dong Wang, Mulin Chen, Xuelong Li

In contrast, we propose a purely passive method to track a person walking in an invisible room by only observing a relay wall, which is more in line with real application scenarios, e. g., security.

Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding

1 code implementation Findings (ACL) 2022 Rui Cao, Yihao Wang, Yuxin Liang, Ling Gao, Jie Zheng, Jie Ren, Zheng Wang

We define a maximum traceable distance metric, through which we learn to what extent the text contrastive learning benefits from the historical information of negative samples.

Contrastive Learning Sentence +4

ESOD:Edge-based Task Scheduling for Object Detection

no code implementations20 Oct 2021 Yihao Wang, Ling Gao, Jie Ren, Rui Cao, Hai Wang, Jie Zheng, Quanli Gao

In detail, we train a DNN model (termed as pre-model) to predict which object detection model to use for the coming task and offloads to which edge servers by physical characteristics of the image task (e. g., brightness, saturation).

Object object-detection +2

Improving Adversarial Robustness for Free with Snapshot Ensemble

no code implementations7 Oct 2021 Yihao Wang

Based on the snapshot ensemble, we present a new method that is easier to implement: unlike original snapshot ensemble that seeks for local minima, our snapshot ensemble focuses on the last few iterations of a training and stores the sets of parameters from them.

Adversarial Robustness

I-Nema: A Biological Image Dataset for Nematode Recognition

1 code implementation15 Mar 2021 Xuequan Lu, Yihao Wang, Sheldon Fung, Xue Qing

In this paper, we identify two main bottlenecks: (1) the lack of a publicly available imaging dataset for diverse species of nematodes (especially the species only found in natural environment) which requires considerable human resources in field work and experts in taxonomy, and (2) the lack of a standard benchmark of state-of-the-art deep learning techniques on this dataset which demands the discipline background in computer science.

Imaging disorder-induced scattering centers in quantum Hall incompressible strip

no code implementations23 Dec 2019 Yihao Wang, Katsushi Hashimoto, Toru Tomimatsu, Yoshiro Hirayama

While the disorder-induced quantum Hall (QH) effect has been studied previously, the effect ofdisorder potential on microscopic features of the integer QH effect remains unclear, particularly forthe incompressible (IC) strip.

Mesoscale and Nanoscale Physics

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