While most existing approaches (e.g., prompt engineering) focus on the LLM's learned representations to patch this performance gap, our experiments actually reveal that LLM representations contain sufficient information to make good

Sentence scoring aims at measuring the likelihood score of a sentence and is widely usedinnatural language processing scenarios, likereranking, which isto select the best sentence from multiple candidates.

In two layer networks, we show how feature learning can dynamically reduce the variance of the final tangent kernel and final network predictions.

A practical guide to training restricted boltzmann machines.

Ultimately, we find that neural networks' behavior on this

However,textgeneration models output tokens sequentially inalargeoutput space; theclassic PATE algorithm is not customized for this setting.

Transformers have shown impressive capabilities across various tasks, but their performance on compositional problems remains a topic of debate. In this work, we investigate the mechanisms of how transformers behave on unseen compositionaltasks.

In label-noise learning, estimating the transition matrix plays an important role in building statistically consistent classifier.