4 citations · 4 across the 5 of their papers we have counts for
5 papers
Diffusion Alignment Beyond KL: Variance Minimisation as Effective Policy Optimiser
Zijing Ou, Jacob Si, Junyi Zhu +4
Diffusion alignment adapts pretrained diffusion models to sample from reward-tilted distributions along the denoising trajectory. This process naturally admits a Sequential Monte C…
ProxyImg: Towards Highly-Controllable Image Representation via Hierarchical Disentangled Proxy Embedding
Ye Chen, Yupeng Zhu, Xiongzhen Zhang +4
Prevailing image representation methods, including explicit representations such as raster images and Gaussian primitives, as well as implicit representations such as latent images…
TabRAG: Improving Tabular Document Question Answering for Retrieval Augmented Generation via Structured Representations
Jacob Si, Mike Qu, Michelle Lee +2
Incorporating external knowledge bases in traditional retrieval-augmented generation (RAG) relies on parsing the document, followed by querying a language model with the parsed inf…
Neural Stochastic Flows: Solver-Free Modelling and Inference for SDE Solutions
Naoki Kiyohara, Edward Johns, Yingzhen Li
Stochastic differential equations (SDEs) are well suited to modelling noisy and irregularly sampled time series found in finance, physics, and machine learning. Traditional approac…
C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion
Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee +3
In deep learning, test-time adaptation has gained attention as a method for model fine-tuning without the need for labeled data. A prime exemplification is the recently proposed te…