6 citations · 13 across the 4 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2025
Policy Gradient Guidance Enables Test Time Control
Jianing Qi, Hao Tang, Zhigang Zhu
We introduce Policy Gradient Guidance (PGG), a simple extension of classifier-free guidance from diffusion models to classical policy gradient methods. PGG augments the policy grad…
cs.LG2024
VerifierQ: Enhancing LLM Test Time Compute with Q-Learning-based Verifiers
Jianing Qi, Hao Tang, Zhigang Zhu
Recent advancements in test time compute, particularly through the use of verifier models, have significantly enhanced the reasoning capabilities of Large Language Models (LLMs). T…
cs.LG2018
Generalizing semi-supervised generative adversarial networks to regression using feature contrasting
Greg Olmschenk, Zhigang Zhu, Hao Tang
In this work, we generalize semi-supervised generative adversarial networks (GANs) from classification problems to regression problems. In the last few years, the importance of imp…