3 papers
cs.CL2025
Relative Scaling Laws for LLMs
William Held, David Hall, Percy Liang +1
Scaling laws describe how language models improve with additional data, parameters, and compute. While widely used, they are typically measured on aggregate test sets. Aggregate ev…
cs.CL2025
AudioJudge: Understanding What Works in Large Audio Model Based Speech Evaluation
Potsawee Manakul, Woody Haosheng Gan, Michael J. Ryan +5
Current speech evaluation suffers from two critical limitations: the need and difficulty of designing specialized systems targeting individual audio characteristics, and poor corre…
cs.CL2025
SynthesizeMe! Inducing Persona-Guided Prompts for Personalized Reward Models in LLMs
Michael J Ryan, Omar Shaikh, Aditri Bhagirath +3
Recent calls for pluralistic alignment of Large Language Models (LLMs) encourage adapting models to diverse user preferences. However, most prior work on personalized reward models…