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cs.LG2025★ 1 cited
Automated Capability Discovery via Foundation Model Self-Exploration
Cong Lu, Shengran Hu, Jeff Clune
Foundation models have become general-purpose assistants, exhibiting diverse capabilities across numerous domains through training on web-scale data. It remains challenging to prec…
cs.LG2024
Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models
Cong Lu, Shengran Hu, Jeff Clune
Go-Explore is a powerful family of algorithms designed to solve hard-exploration problems built on the principle of archiving discovered states, and iteratively returning to and ex…
cs.LG2021
Accelerating Multi-Objective Neural Architecture Search by Random-Weight Evaluation
Shengran Hu, Ran Cheng, Cheng He +3
For the goal of automated design of high-performance deep convolutional neural networks (CNNs), Neural Architecture Search (NAS) methodology is becoming increasingly important for…