62 citations · 104 across the 24 of their papers we have counts for
3 papers · 1 filter
Will Scaling Improve Social Simulation with LLMs?
Caleb Ziems, William Held, Su Doga Karaca +3
Large Language Model (LLM) social simulations are a promising research method, but they are not yet faithful enough to be adopted widely. In this work, we investigate whether the c…
Putting HUMANS first: Efficient LAM Evaluation with Human Preference Alignment
Woody Haosheng Gan, William Held, Diyi Yang
The rapid proliferation of large audio models (LAMs) demands efficient approaches for model comparison, yet comprehensive benchmarks are costly. To fill this gap, we investigate wh…
Scaling Open Discrete Audio Foundation Models with Interleaved Semantic, Acoustic, and Text Tokens
Potsawee Manakul, Woody Haosheng Gan, Martijn Bartelds +3
Current audio language models are predominantly text-first, either extending pre-trained text LLM backbones or relying on semantic-only audio tokens, limiting general audio modelin…