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pro vyhledávání: '"Chan, Joel"'
Sharing, reusing, and synthesizing knowledge is central to the research process, both individually, and with others. These core functions are not supported by our formal scholarly publishing infrastructure: instead of the smooth functioning of functi
Externí odkaz:
http://arxiv.org/abs/2407.20666
Autor:
Ding, Zijian, Chan, Joel
Complex data analysis inherently seeks unexpected insights through exploratory visual analysis methods, transcending logical, step-by-step processing. However, existing interfaces such as notebooks and dashboards have limitations in exploration and c
Externí odkaz:
http://arxiv.org/abs/2402.08812
Interactive systems that facilitate exposure to examples can augment problem solving performance. However designers of such systems are often faced with many practical design decisions about how users will interact with examples, with little clear th
Externí odkaz:
http://arxiv.org/abs/2401.11022
Autor:
Emuna, Hen, Borenstein, Nadav, Qian, Xin, Kang, Hyeonsu, Chan, Joel, Kittur, Aniket, Shahaf, Dafna
Biologically Inspired Design (BID), or Biomimicry, is a problem-solving methodology that applies analogies from nature to solve engineering challenges. For example, Speedo engineers designed swimsuits based on shark skin. Finding relevant biological
Externí odkaz:
http://arxiv.org/abs/2312.12681
Autor:
Ding, Zijian, Chan, Joel
Large Language Models (LLMs) have demonstrated impressive text generation capabilities, prompting us to reconsider the future of human-AI co-creation and how humans interact with LLMs. In this paper, we present a spectrum of content generation tasks
Externí odkaz:
http://arxiv.org/abs/2303.06430
Cross-domain analogical reasoning is a core creative ability that can be challenging for humans. Recent work has shown some proofs-of concept of Large language Models' (LLMs) ability to generate cross-domain analogies. However, the reliability and po
Externí odkaz:
http://arxiv.org/abs/2302.12832
Analogies have been central to creative problem-solving throughout the history of science and technology. As the number of scientific papers continues to increase exponentially, there is a growing opportunity for finding diverse solutions to existing
Externí odkaz:
http://arxiv.org/abs/2205.15476
Autor:
Hope, Tom, Tamari, Ronen, Kang, Hyeonsu, Hershcovich, Daniel, Chan, Joel, Kittur, Aniket, Shahaf, Dafna
Publikováno v:
CHI 2022
Large repositories of products, patents and scientific papers offer an opportunity for building systems that scour millions of ideas and help users discover inspirations. However, idea descriptions are typically in the form of unstructured text, lack
Externí odkaz:
http://arxiv.org/abs/2102.09761
Autor:
Qian, Xin, Rossi, Ryan A., Du, Fan, Kim, Sungchul, Koh, Eunyee, Malik, Sana, Lee, Tak Yeon, Chan, Joel
Visualization recommendation seeks to generate, score, and recommend to users useful visualizations automatically, and are fundamentally important for exploring and gaining insights into a new or existing dataset quickly. In this work, we propose the
Externí odkaz:
http://arxiv.org/abs/2009.12316
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