Summary of Rtify: Aligning Deep Neural Networks with Human Behavioral Decisions, by Yu-ang Cheng et al.
RTify: Aligning Deep Neural Networks with Human Behavioral Decisions
by Yu-Ang Cheng, Ivan Felipe Rodriguez, Sixuan Chen, Kohitij Kar, Takeo Watanabe, Thomas Serre
First submitted to arxiv on: 6 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Neurons and Cognition (q-bio.NC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed computational framework aims to better model the dynamics of human behavioral choices in primate vision by learning to align recurrent neural network (RNN) temporal dynamics with human reaction times. The approach constrains the number of time steps an RNN takes to solve a task using human RTs, allowing for optimal tradeoffs between speed and accuracy without requiring human data. This framework is evaluated against various psychophysics experiments and is found to account well for human RT data. Additionally, the approximation is used to train a deep learning implementation of the Wong-Wang decision-making model, which is integrated with a convolutional neural network (CNN) model of visual processing and tested using both artificial and natural image stimuli. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A team of researchers has developed a new way to understand how humans make decisions. They created a special kind of computer program that can mimic human behavior when making choices. This program, called a recurrent neural network (RNN), is designed to work like the human brain. The RNN is trained using data about how long it takes humans to react to certain stimuli, and this helps the program make better decisions. The researchers tested their program against real-world experiments and found that it worked well. They also used this approach to train a separate program that can be used for image recognition tasks. |
Keywords
» Artificial intelligence » Cnn » Deep learning » Neural network » Rnn
