316 citations · 2.3k across the 42 of their papers we have counts for
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cs.LG2026
An all-transistor physical-learning transformer can be trained to perform in-context learning
Michael C. Abbott, Benjamin B. Machta
Most systems trained by equilibrium propagation or coupled learning are in the same class as multi-layer perceptrons: while they may be universal function approximators, they strug…
cs.LG2025★ 2 cited
In-Context Learning can distort the relationship between sequence likelihoods and biological fitness
Pranav Kantroo, Günter P. Wagner, Benjamin B. Machta
Language models have emerged as powerful predictors of the viability of biological sequences. During training these models learn the rules of the grammar obeyed by sequences of ami…