Search Results for author: Yiwei Yang

Found 6 papers, 4 papers with code

KEN: Kernel Extensions using Natural Language

1 code implementation9 Dec 2023 Yusheng Zheng, Yiwei Yang, Maolin Chen, Andrew Quinn

In particular, the system uses symbolic execution in a novel structure that allows it to combine the results of program synthesis and program comprehension and build on the recent success that LLMs have shown for each of these tasks individually.

Program Synthesis

Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias

1 code implementation21 Dec 2022 Robert Wolfe, Yiwei Yang, Bill Howe, Aylin Caliskan

A first experiment uses standardized images of women from the Sexual OBjectification and EMotion Database, and finds that human characteristics are disassociated from images of objectified women: the model's recognition of emotional state is mediated by whether the subject is fully or partially clothed.

Attack as Defense: Characterizing Adversarial Examples using Robustness

1 code implementation13 Mar 2021 Zhe Zhao, Guangke Chen, Jingyi Wang, Yiwei Yang, Fu Song, Jun Sun

Though various defense mechanisms have been proposed to improve robustness of deep learning software, many of them are ineffective against adaptive attacks.

FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images

no code implementations28 Jul 2019 Yunhe Gao, Rui Huang, Ming Chen, Zhe Wang, Jincheng Deng, YuanYuan Chen, Yiwei Yang, Jie Zhang, Chanjuan Tao, Hongsheng Li

In this paper, we propose an end-to-end deep neural network for solving the problem of imbalanced large and small organ segmentation in head and neck (HaN) CT images.

Organ Segmentation Segmentation

HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop

no code implementations ACL 2019 Yiwei Yang, Eser Kandogan, Yunyao Li, Walter S. Lasecki, Prithviraj Sen

While the role of humans is increasingly recognized in machine learning community, representation of and interaction with models in current human-in-the-loop machine learning (HITL-ML) approaches are too low-level and far-removed from human's conceptual models.

BIG-bench Machine Learning

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