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Mohit Yadav

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#large language models Open access Sep 2026

DPO vs. RLHF: An Empirical Comparison of Alignment Techniques for Large Language Models

This work presents a reproducible empirical comparison of Direct Preference Optimization (DPO) and Reinforcement Learning from Human Feedback (RLHF) for Large Language Model alignment. Experiments are conducted on GPT-2 (124M parameters) using the Anthropic HH-RLHF dataset. The study evaluates alignment quality, reward...

Mohit Yadav · Zenodo (CERN European Organi... · 0 citations