Objective Mismatch in Reinforcement Learning from Human Feedback: Acknowledgments, and References

Machine Learning Tech Brief By HackerNoon

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This conclusion highlights the path toward enhanced accessibility and reliability for language models.
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Discover the challenges of objective mismatch in RLHF for large language models, affecting the alignment between reward models and downstream performance. This paper explores the origins, manifestations, and potential solutions to address this issue, connecting insights from NLP and RL literature. Gain insights into fostering better RLHF practices for more effective and user-aligned language models.