Beyond the Turing Test

By Itamar Arel, Scott Livingston. 2009

144 citations recorded by the source corpus.

Subfields: Information Systems and Management, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems and Management

1. Noël Crespi
2. Antonia F. de C. Hamilton
3. G. Lee
4. Roberto Minerva
5. Richard Socher
6. Shane Legg
7. Xueni Pan

In Natural Language Processing

1. Dawn Song
2. Nitish Shirish Keskar
3. Richard Socher
4. Mohit Bansal
5. Quoc V. Le
6. Felix Hill
7. Caiming Xiong
8. Dan Hendrycks

Citations in the corpus

• Measuring Mathematical Problem Solving With the MATH Dataset (2021, background): “We also find that Transformers also do well on the C-Test, a pattern completion test that has a 77% correlation with human IQ (Hernández-Orallo, 2000).”
• Measuring abstract reasoning in neural networks (2018, background): “There is prior work emphasising both the advantages (Clark & Etzioni, 2016) and limitations (Davis, 2014) of apply-Measuring ing standardized tests in AI (see Marcus et al. (2016) and contributed articles for a review).”
• Meta-learning of Sequential Strategies (2019, background): “Achieving this generality (or universality) is considered by many research agendas to be one of the core challenges in artificial intelligence (AI) [Solomonoff, 1964, Gottfredson, 1997, Hernandez-Orallo, 2000, Hutter, 2004].”
• Why and how to use virtual reality to study human social interaction: The challenges of exploring a new research landscape (2018, methodology): “A chatbot recently ‘passed’ this test, albeit using tricks including pretending to be a child from a different country, rather than by showing adult levels of behaviour (You, 2015).”
• Pretrained AI Models: Performativity, Mobility, and Change (2019, background): “As such, several alternatives have recently been proposed [59].”
• An Approximation of the Universal Intelligence Measure (2011, background): “Related discussion on the motivation behind such tests is given by Dowe and Hajek (1998); Hern´andez-Orallo (2000); Schaul et al. (2011).”
• Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020, methodology): “Grieves proposes, for the DT, a test similar to the one proposed by Alan Turing for the Artificial Intelligent systems [22]: the indistinguishability of the two objects.”