10 citations · 10 across the 18 of their papers we have counts for
4 papers · 2 filters
A Minimalist Method for Fine-tuning Text-to-Image Diffusion Models
Yanting Miao, William Loh, Pacal Poupart +1
Recent work uses reinforcement learning (RL) to fine-tune text-to-image diffusion models, improving text-image alignment and sample quality. However, existing approaches introduce…
Basis Transformers for Multi-Task Tabular Regression
Wei Min Loh, Jiaqi Shang, Pascal Poupart
Dealing with tabular data is challenging due to partial information, noise, and heterogeneous structure. Existing techniques often struggle to simultaneously address key aspects of…
Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling
Gustavo Sutter Pessurno de Carvalho, Mohammed Abdulrahman, Hao Wang +7
The optimization of expensive black-box functions is ubiquitous in science and engineering. A common solution to this problem is Bayesian optimization (BO), which is generally comp…
Towards Cost-Effective Reward Guided Text Generation
Ahmad Rashid, Ruotian Wu, Rongqi Fan +3
Reward-guided text generation (RGTG) has emerged as a viable alternative to offline reinforcement learning from human feedback (RLHF). RGTG methods can align baseline language mode…