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Large Language Models

Capture the Flag: Uncovering Data Insights with Large Language Models
The extraction of a small number of relevant insights from vast amounts of data is a crucial component of data-driven decision-making. …
Lag-Llama: A Foundation Model for Probabilistic Time Series Forecasting
In this work, we present Lag-Llama, a general-purpose probabilistic time series forecasting model trained on a large collection of time …
The Unsolved Challenges of LLMs in Open-Ended Web Tasks: A Case Study
In this work, we investigate the challenges associated with developing goal-driven AI agents capable of performing open-ended tasks in …
LLM aided semi-supervision for efficient Extractive Dialog Summarization
Generating high-quality summaries for chat dialogs often requires large labeled datasets. We propose a method to efficiently use …
MAGNIFICO: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretations
Humans possess a remarkable ability to assign novel interpretations to linguistic expressions, enabling them to learn new words and …
PromptMix: A Class Boundary Augmentation Method for Large Language Model Distillation
Data augmentation is a widely used technique to address the problem of text classification when there is a limited amount of training …
Equivariant Adaptation of Large Pre-Trained Models
Equivariant networks are specifically designed to ensure consistent behavior with respect to a set of input transformations, leading to …
Causal Discovery with Language Models as Imperfect Experts
Understanding the causal relationships that underlie a system is a fundamental prerequisite to accurate decision-making. In this work, …
BigCode Governance Card

The BigCode Governance Card serves as an overview of the different mechanisms and areas of governance in the BigCode project. It aims …