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Found 5 papers, 1 papers with code
Uncovering Latent Human Wellbeing in Language Model Embeddings
Do language models implicitly learn a concept of human wellbeing?
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
Reinforcement learning from human feedback (RLHF) is a technique for training AI systems to align with human goals.
Computational Complexity Evaluation of Neural Network Applications in Signal Processing
We provide and link four software-to-hardware complexity measures, defining how the different complexity metrics relate to the layers' hyper-parameters.
Benefits of Assistance over Reward Learning
By merging reward learning and control, assistive agents can reason about the impact of control actions on reward learning, leading to several advantages over agents based on reward learning.
DERAIL: Diagnostic Environments for Reward And Imitation Learning
We evaluate a range of common reward and imitation learning algorithms on our tasks.
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