Raven Progressive Matrices

By John, J. Raven. 2003

618 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Developmental and Educational Psychology, Experimental and Cognitive Psychology, Evaluation & Benchmarks, Cognitive Science & Psychology

How researchers see this paper

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

In Artificial Intelligence

1. Josh Tenenbaum
2. Maxwell Nye
3. Armando Solar-Lezama
4. Kevin Ellis
5. Catherine Wong
6. Miguel L'azaro-Gredilla
7. Dileep George
8. Luke B. Hewitt

In Developmental and Educational Psychology

1. Miguel L'azaro-Gredilla
2. Josh Tenenbaum
3. J. Swaroop Guntupalli
4. Dianhuan Lin
5. Dileep George
6. Tomer D. Ullman
7. T. Griffiths
8. Noah D. Goodman

In Experimental and Cognitive Psychology

1. Miguel L'azaro-Gredilla
2. Josh Tenenbaum
3. J. Swaroop Guntupalli
4. Dianhuan Lin
5. Dileep George

In Evaluation & Benchmarks

1. Miguel L'azaro-Gredilla
2. Armando Solar-Lezama
3. Catherine Wong
4. Josh Tenenbaum
5. J. Swaroop Guntupalli
6. Dianhuan Lin
7. Dileep George
8. Maxwell Nye

In Cognitive Science & Psychology

1. Miguel L'azaro-Gredilla
2. Josh Tenenbaum
3. J. Swaroop Guntupalli
4. Dianhuan Lin
5. Dileep George
6. Maxwell Nye
7. Tomer D. Ullman
8. Brenden M. Lake

Citations in the corpus

• Beyond imitation: Zero-shot task transfer on robots by learning concepts as cognitive programs (2018, methodology): “sure conceptual and abstract reasoning have drawbacks that prevent them from being used in a study for acquiring and representing concepts as sensorimotor programs. Raven’s progressive matrices (RPM) (53) are often used as a test for conceptual representation. Instead of using RPM, we chose to use t”
• DreamCoder: growing generalizable, interpretable knowledge with wake–sleep Bayesian program learning (2020, background): “Procedural or generative visual concepts — from Bongard problems (25), to handwritten characters (5, 26), to Raven’s progressive matrices (27) — are studied across AI and cognitive science, because they offer a bridge between low-level perception and high-level reasoning.”
• The Measure of Intelligence (2019, neutral): “is targeted at both humans and artifi- cially intelligent systems that aim at emulating a human-like form of general fluid intelligence. It is somewhat similar in format to Raven’s Progressive Matrices [47], a classic IQ test format going back to the 1930s. ARC has the following top-level goals: Stay ”