Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
ABC-Align: Prediction-Powered Alignment with Adaptive Bias Control
Eric Frankel, Banghua Zhu, Sewoong Oh +1
Language model post-training is often bottlenecked by the need for human-collected preference data, which is expensive and difficult to scale. Reinforcement learning from AI feedba…
cs.LG2025
dUltra: Ultra-Fast Diffusion Language Models via Reinforcement Learning
Shirui Chen, Jiantao Jiao, Lillian J. Ratliff +1
Masked diffusion language models (MDLMs) offer the potential for parallel token generation, but most open-source MDLMs decode fewer than 5 tokens per model forward pass even with s…
cs.LG2025
S4S: Solving for a Diffusion Model Solver
Eric Frankel, Sitan Chen, Jerry Li +3
Diffusion models (DMs) create samples from a data distribution by starting from random noise and iteratively solving a reverse-time ordinary differential equation (ODE). Because ea…