What Does the Future of AI Model Training Hold?

Table of Links

Abstract and 1 Introduction

2 Preliminaries

2.1 RLHF Based on Reward Models

2.2 RLHF with General Preferences

3 Direct Nash Optimization and 3.1 Derivation of Algorithm 1

3.2 Theoretical Analysis

4 Practical Algorithm – Iterative Contrastive Self-Improvement

5 Experiments and 5.1 Experimental Setup

5.2 Results and Analysis

6 Related Work

7 Conclusion and References

Appendix

A Extension to Regularized Preferences

B Detailed Proofs

C Additional Experimental Details

7 Conclusion

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