Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Fast, Ethan"'
Autor:
Annessi, Robert, Fast, Ethan
Decentralized cryptocurrency exchanges offer compelling security benefits over centralized exchanges: users control their funds and avoid the risk of an exchange hack or malicious operator. However, because user assets are fully accessible by a secre
Externí odkaz:
http://arxiv.org/abs/2106.10972
Today's conversational agents are restricted to simple standalone commands. In this paper, we present Iris, an agent that draws on human conversational strategies to combine commands, allowing it to perform more complex tasks that it has not been exp
Externí odkaz:
http://arxiv.org/abs/1707.05015
Autor:
Fast, Ethan, Horvitz, Eric
Analyses of text corpora over time can reveal trends in beliefs, interest, and sentiment about a topic. We focus on views expressed about artificial intelligence (AI) in the New York Times over a 30-year period. General interest, awareness, and discu
Externí odkaz:
http://arxiv.org/abs/1609.04904
Autor:
Fast, Ethan, Horvitz, Eric
We explore linguistic and behavioral features of dogmatism in social media and construct statistical models that can identify dogmatic comments. Our model is based on a corpus of Reddit posts, collected across a diverse set of conversational topics a
Externí odkaz:
http://arxiv.org/abs/1609.00425
Imagine a princess asleep in a castle, waiting for her prince to slay the dragon and rescue her. Tales like the famous Sleeping Beauty clearly divide up gender roles. But what about more modern stories, borne of a generation increasingly aware of soc
Externí odkaz:
http://arxiv.org/abs/1603.08832
Human language is colored by a broad range of topics, but existing text analysis tools only focus on a small number of them. We present Empath, a tool that can generate and validate new lexical categories on demand from a small set of seed terms (lik
Externí odkaz:
http://arxiv.org/abs/1602.06979
From smart homes that prepare coffee when we wake, to phones that know not to interrupt us during important conversations, our collective visions of HCI imagine a future in which computers understand a broad range of human behaviors. Today our system
Externí odkaz:
http://arxiv.org/abs/1602.06977
Neutral landscapes and mutational robustness are believed to be important enablers of evolvability in biology. We apply these concepts to software, defining mutational robustness to be the fraction of random mutations that leave a program's behavior
Externí odkaz:
http://arxiv.org/abs/1204.4224
Akademický článek
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Autor:
Fast, Ethan, Horvitz, Eric
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 31
Analyses of text corpora over time can reveal trends in beliefs, interest, and sentiment about a topic. We focus on views expressed about artificial intelligence (AI) in the New York Times over a 30-year period. General interest, awareness, and discu