Text Generation aims to produce plausible and readable text in human language from input
data. The resurgence of deep learning has greatly advanced this field, in particular, with the …

This paper delves into the pivotal role of prompt engineering in unleashing the capabilities
of Large Language Models (LLMs). Prompt engineering is the process of structuring input …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

This article presents a comprehensive and practical guide for practitioners and end-users
working with Large Language Models (LLMs) in their downstream Natural Language …

Abstract Large Language Models (LLMs) can achieve strong performance on many tasks by
producing step-by-step reasoning before giving a final output, often referred to as chain-of …

In recent years, large language models have greatly improved in their ability to perform
complex multi-step reasoning. However, even state-of-the-art models still regularly produce …

Reinforcement learning from human feedback (RLHF) is a technique for training AI systems
to align with human goals. RLHF has emerged as the central method used to finetune state …

Ensuring alignment, which refers to making models behave in accordance with human
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …

Large language models (LLMs), such as GPT-4, have shown remarkable performance in
natural language processing (NLP) tasks, including challenging mathematical reasoning …

Reinforcement learning from human feedback (RLHF) can improve the quality of large
language model's (LLM) outputs by aligning them with human preferences. We propose a …