Large Language Models
We present TapeAgents, an agent framework that leverages a structured, replayable log (tape) of the agent session to facilitate all …
This document serves as an overview of the different mechanisms and areas of governance in the BigCode project. It aims to support …
The extraction of a small number of relevant insights from vast amounts of data is a crucial component of data-driven decision-making. …
In this work, we present Lag-Llama, a general-purpose probabilistic time series forecasting model trained on a large collection of time …
In this work, we investigate the challenges associated with developing goal-driven AI agents capable of performing open-ended tasks in …
Generating high-quality summaries for chat dialogs often requires large labeled datasets. We propose a method to efficiently use …
Humans possess a remarkable ability to assign novel interpretations to linguistic expressions, enabling them to learn new words and …
Data augmentation is a widely used technique to address the problem of
text classification when there is a limited amount of training …
Equivariant networks are specifically designed to ensure consistent behavior with respect to a set of input transformations, leading to …
