V Bengs: Researcher — Prolific Citations Library

Explore 1 peer-reviewed study by V Bengs in Reinforcement Learning from Human Feedback (RLHF) and LLM (2024). Discover research powered by Prolific's participant panel.

This page lists 1 peer-reviewed paper authored or co-authored by V Bengs in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (1 of 1)

A survey of reinforcement learning from human feedback

Authors: T Kaufmann, P Weng, V Bengs, E Hüllermeier

Year: 2024

Published in: 2024 - epub.ub.uni-muenchen.de

Institution: Paderborn University, German Research Center for Artificial Intelligence (DFKI), Duke Kunshan University

Research Area: Reinforcement Learning from Human Feedback (RLHF), LLM, Reward Modeling

Discipline: Artificial Intelligence

This paper surveys the fundamentals, diverse applications, and evolving impact of reinforcement learning from human feedback (RLHF), emphasizing its role in improving intelligent system alignment and performance.

Methods: The paper utilizes a survey-based approach to synthesize existing research, exploring the interactions between reinforcement learning algorithms and human input.

Key Findings: The study examines the principles, dynamics, applications, and trends in RLHF, offering insights into its role in enhancing large language models (LLMs) and intelligent systems.

Citations: 354