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cs.SD2026
Same Words, Different Judgments: How Preferences Vary Across Modalities
Aaron Broukhim, Nadir Weibel, Eshin Jolly
Preference-based reinforcement learning (PbRL) is the dominant framework for aligning AI systems to human preferences. However, evaluation protocols for such data were designed for…
cs.SD2025
Preference-Based Learning in Audio Applications: A Systematic Analysis
Aaron Broukhim, Yiran Shen, Prithviraj Ammanabrolu +1
Despite the parallel challenges that audio and text domains face in evaluating generative model outputs, preference learning remains remarkably underexplored in audio applications.…