37 citations · 79 across the 12 of their papers we have counts for
6 papers · 1 filter
Unified Text-Image Generation with Weakness-Targeted Post-Training
Jiahui Chen, Philippe Hansen-Estruch, Xiaochuang Han +7
Unified multimodal generation architectures that jointly produce text and images have recently emerged as a promising direction for text-to-image (T2I) synthesis. However, many exi…
Improving the Physics of Video Generation with VJEPA-2 Reward Signal
Jianhao Yuan, Xiaofeng Zhang, Felix Friedrich +7
This is a short technical report describing the winning entry of the PhysicsIQ Challenge, presented at the Perception Test Workshop at ICCV 2025. State-of-the-art video generative…
Increasing the Utility of Synthetic Images through Chamfer Guidance
Nicola Dall'Asen, Xiaofeng Zhang, Reyhane Askari Hemmat +4
Conditional image generative models hold considerable promise to produce infinite amounts of synthetic training data. Yet, recent progress in generation quality has come at the exp…
Improving Geo-diversity of Generated Images with Contextualized Vendi Score Guidance
Reyhane Askari Hemmat, Melissa Hall, Alicia Sun +3
With the growing popularity of text-to-image generative models, there has been increasing focus on understanding their risks and biases. Recent work has found that state-of-the-art…
Feedback-guided Data Synthesis for Imbalanced Classification
Reyhane Askari Hemmat, Mohammad Pezeshki, Florian Bordes +2
Current status quo in machine learning is to use static datasets of real images for training, which often come from long-tailed distributions. With the recent advances in generativ…
QReg: On Regularization Effects of Quantization
MohammadHossein AskariHemmat, Reyhane Askari Hemmat, Alex Hoffman +6
In this paper we study the effects of quantization in DNN training. We hypothesize that weight quantization is a form of regularization and the amount of regularization is correlat…