The design and optimization of functional proteins that bind specific ligand molecules is paramount in therapeutics and bio-engineering.

However, it is unclear how the style-independence property benefits ACL-learned robust representations.

The dynamics of neural activity are described by a standard rate model. Note that only the third term of Eq. 'th place cell preferred firing position in the's are standard unit vectors spanning an orthonormal basis. To derive Eq. 3 we evaluate the derivative of Energy landscapes were uniformly shifted throughout the manuscript by a constant (Figs. For each network with a different number of total embedded maps, 15 realizations were performed in which the permutations between the spatial maps were chosen independently and at random. Code availability Code is available at public repository https://doi.org/10.5281/zenodo.10016179.

In some cases, it is thought that the synaptic connectivity supports multiple attractor manifolds, each mapped to a different context or task.

Modern neural network design typically follows a "larger is better" rule of thumb, with models

However, the simple power-law relation becomes more complicated when compute is considered.

Through considerable effort and intuition, several recent works have reverse-engineered nontrivial behaviors of transformer models. This paper systematizes the mechanistic interpretability process they followed. First, researchers choose a metric and dataset that elicit the desired model behavior.

In human-AI collaboration systems for critical applications, in order to ensure minimal error, users should set an operating point based on model confidence to determine when the decision should be delegated to human experts.