Papers with ADPO algorithm

1 papers
Adversarial DPO: Harnessing Harmful Data for Reducing Toxicity with Minimal Impact on Coherence and Evasiveness in Dialogue Agents (2024.findings-naacl)

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Challenge: Existing toxicity within large language models can negatively impact the user experience, causing performance degradation.
Approach: They propose an adversarial DPO algorithm that improves direct preference optimization (DPO) by incorporating harmful data into the generative model.
Outcome: The proposed training algorithm improves the model’s resilience against harmful conversations while minimizing performance degradation.

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