Significant focus has been placed on integrating large language models (LLMs) with various tools in developing general-purpose agents.

In this paper, we propose an efficient algorithm to accelerate computing the TT decomposition with the Alternating Least Squares (ALS) algorithm relying on exact leverage scores sampling.

We revisit this scenario as an experimental case study in Section 6.

Unlike humans, these ' Large Language Models ' (LLMs) are highly sensitive to small changes in their inputs, leading to unwanted inconsistency in their behavior.

Uncertainty is introduced in optimized DNNs through stochastic algorithms, forming specific distributions.