FIESTA uses bandit algorithms to adaptively decide how many seeds and splits to run for each candidate model, focusing effort on promising ones while providing guarantees on selecting the optimal model.
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Pref-CTRL trains a multi-objective value function on preferences to guide representation editing for LLM alignment, outperforming RE-Control on benchmarks with better out-of-domain generalization.
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FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms
FIESTA uses bandit algorithms to adaptively decide how many seeds and splits to run for each candidate model, focusing effort on promising ones while providing guarantees on selecting the optimal model.
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Pref-CTRL: Preference Driven LLM Alignment using Representation Editing
Pref-CTRL trains a multi-objective value function on preferences to guide representation editing for LLM alignment, outperforming RE-Control on benchmarks with better out-of-domain generalization.