2 papers
cs.CL2025
Sparsity May Be All You Need: Sparse Random Parameter Adaptation
Jesus Rios, Pierre Dognin, Ronny Luss +1
Full fine-tuning of large language models for alignment and task adaptation has become prohibitively expensive as models have grown in size. Parameter-Efficient Fine-Tuning (PEFT)…
cs.CL2025
Evaluating the Prompt Steerability of Large Language Models
Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy +5
Building pluralistic AI requires designing models that are able to be shaped to represent a wide range of value systems and cultures. Achieving this requires first being able to ev…