3 Search Results for "Zhang, Bo"

Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.93
The Ethics of AI-Generated Maps: DALL·E 2 and AI’s Implications for Cartography (Short Paper)

Authors: Qianheng Zhang, Yuhao Kang, and Robert Roth

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
The rapid advancement of artificial intelligence (AI) such as the emergence of large language models ChatGPT and DALL·E 2 has brought both opportunities for improving productivity and raised ethical concerns. This paper investigates the ethics of using artificial intelligence (AI) in cartography, with a particular focus on the generation of maps using DALL·E 2. To accomplish this, we first created an open-sourced dataset that includes synthetic (AI-generated) and real-world (human-designed) maps at multiple scales with a variety of settings. We subsequently examined four potential ethical concerns that may arise from the characteristics of DALL·E 2 generated maps, namely inaccuracies, misleading information, unanticipated features, and irreproducibility. We then developed a deep learning-based model to identify those AI-generated maps. Our research emphasizes the importance of ethical considerations in the development and use of AI techniques in cartography, contributing to the growing body of work on trustworthy maps. We aim to raise public awareness of the potential risks associated with AI-generated maps and support the development of ethical guidelines for their future use.
Cite as

Qianheng Zhang, Yuhao Kang, and Robert Roth. The Ethics of AI-Generated Maps: DALL·E 2 and AI’s Implications for Cartography (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 93:1-93:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{zhang_et_al:LIPIcs.GIScience.2023.93,
  author =	{Zhang, Qianheng and Kang, Yuhao and Roth, Robert},
  title =	{{The Ethics of AI-Generated Maps: DALL·E 2 and AI’s Implications for Cartography}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{93:1--93:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.93},
  URN =		{urn:nbn:de:0030-drops-189886},
  doi =		{10.4230/LIPIcs.GIScience.2023.93},
  annote =	{Keywords: Ethics, GeoAI, DALL-E, Cartography}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.CONCUR.2018.4
Verifying Arithmetic Assembly Programs in Cryptographic Primitives (Invited Talk)

Authors: Andy Polyakov, Ming-Hsien Tsai, Bow-Yaw Wang, and Bo-Yin Yang

Published in: LIPIcs, Volume 118, 29th International Conference on Concurrency Theory (CONCUR 2018)

Abstract
Arithmetic over large finite fields is indispensable in modern cryptography. For efficienty, these operations are often implemented in manually optimized assembly programs. Since these arithmetic assembly programs necessarily perform lots of non-linear computation, checking their correctness is a challenging verification problem. We develop techniques to verify such programs automatically in this paper. Using our techniques, we have successfully verified a number of assembly programs in OpenSSL. Moreover, our tool verifies the boringSSL Montgomery Ladderstep (about 1400 assembly instructions) in 1 hour. This is by far the fastest verification technique for such programs.
Cite as

Andy Polyakov, Ming-Hsien Tsai, Bow-Yaw Wang, and Bo-Yin Yang. Verifying Arithmetic Assembly Programs in Cryptographic Primitives (Invited Talk). In 29th International Conference on Concurrency Theory (CONCUR 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 118, pp. 4:1-4:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{polyakov_et_al:LIPIcs.CONCUR.2018.4,
  author =	{Polyakov, Andy and Tsai, Ming-Hsien and Wang, Bow-Yaw and Yang, Bo-Yin},
  title =	{{Verifying Arithmetic Assembly Programs in Cryptographic Primitives}},
  booktitle =	{29th International Conference on Concurrency Theory (CONCUR 2018)},
  pages =	{4:1--4:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-087-3},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{118},
  editor =	{Schewe, Sven and Zhang, Lijun},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2018.4},
  URN =		{urn:nbn:de:0030-drops-95425},
  doi =		{10.4230/LIPIcs.CONCUR.2018.4},
  annote =	{Keywords: Formal verification, Cryptography, Assembly Programs}
}
Document
DOI: 10.4230/DARTS.3.1.1
Hadoop-Benchmark: Rapid Prototyping and Evaluation of Self-Adaptive Behaviors in Hadoop Clusters (Artifact)

Authors: Bo Zhang, Filip Krikava, Romain Rouvoy, and Lionel Seinturier

Published in: DARTS, Volume 3, Issue 1, Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017)

Abstract
Arising with the popularity of Hadoop, optimizing Hadoop executions has grabbed lots of attention from research community. Many research contributions are proposed to elevate Hadoop performance, particularly in the domain of self-adaptive software systems. However, due to the complexity of Hadoop operation and the difficulty to reproduce experiments, the efforts of these Hadoop-related research are hard to be evaluated. To address this limitation, we propose a research acceleration platform for rapid prototyping and evaluation of self-adaptive behavior in Hadoop clusters. It provides an automated manner to quickly and easily provision reproducible Hadoop environments and execute acknowledged benchmarks. This platform is based on the state-of-the-art container technology that supports both distributed configurations as well as standalone single-host setups. We demonstrate the approach on a complete implementation of a concrete Hadoop self-adaptive case study.
Cite as

Bo Zhang, Filip Krikava, Romain Rouvoy, and Lionel Seinturier. Hadoop-Benchmark: Rapid Prototyping and Evaluation of Self-Adaptive Behaviors in Hadoop Clusters (Artifact). In Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017). Dagstuhl Artifacts Series (DARTS), Volume 3, Issue 1, pp. 1:1-1:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@Article{zhang_et_al:DARTS.3.1.1,
  author =	{Zhang, Bo and Krikava, Filip and Rouvoy, Romain and Seinturier, Lionel},
  title =	{{Hadoop-Benchmark: Rapid Prototyping and Evaluation of Self-Adaptive Behaviors in Hadoop Clusters (Artifact)}},
  pages =	{1:1--1:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2017},
  volume =	{3},
  number =	{1},
  editor =	{Zhang, Bo and Krikava, Filip and Rouvoy, Romain and Seinturier, Lionel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DARTS.3.1.1},
  URN =		{urn:nbn:de:0030-drops-71392},
  doi =		{10.4230/DARTS.3.1.1},
  annote =	{Keywords: Hadoop, Docker, Rapid Prototyping, Benchmark}
}
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