141 citations · 162 across the 4 of their papers we have counts for
4 papers
PolyAlign: Conditional Human-Distribution Alignment
L. D. M. S. Sai Teja, Ufaq Khan, Sathira Silva +2
Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective fo…
Estimating Q(s,s') with Deep Deterministic Dynamics Gradients
Ashley D. Edwards, Himanshu Sahni, Rosanne Liu +7
In this paper, we introduce a novel form of value function, , that expresses the utility of transitioning from a state to a neighboring state and then acting opt…
Plug and Play Language Models: A Simple Approach to Controlled Text Generation
Sumanth Dathathri, Andrea Madotto, Janice Lan +5
Large transformer-based language models (LMs) trained on huge text corpora have shown unparalleled generation capabilities. However, controlling attributes of the generated languag…
Metropolis-Hastings Generative Adversarial Networks
Ryan Turner, Jane Hung, Eric Frank +2
We introduce the Metropolis-Hastings generative adversarial network (MH-GAN), which combines aspects of Markov chain Monte Carlo and GANs. The MH-GAN draws samples from the distrib…