32 citations · 169 across the 16 of their papers we have counts for
17 papers
ImageCaptioner: Image Captioner for Image Captioning Bias Amplification Assessment
Eslam Mohamed Bakr, Pengzhan Sun, Li Erran Li +1
Most pre-trained learning systems are known to suffer from bias, which typically emerges from the data, the model, or both. Measuring and quantifying bias and its sources is a chal…
Attribute-Centric Compositional Text-to-Image Generation
Yuren Cong, Martin Renqiang Min, Li Erran Li +2
Despite the recent impressive breakthroughs in text-to-image generation, generative models have difficulty in capturing the data distribution of underrepresented attribute composit…
Neural Attentive Circuits
Nasim Rahaman, Martin Weiss, Francesco Locatello +5
Recent work has seen the development of general purpose neural architectures that can be trained to perform tasks across diverse data modalities. General purpose models typically m…
Value Memory Graph: A Graph-Structured World Model for Offline Reinforcement Learning
Deyao Zhu, Li Erran Li, Mohamed Elhoseiny
Reinforcement Learning (RL) methods are typically applied directly in environments to learn policies. In some complex environments with continuous state-action spaces, sparse rewar…
A Causal Lens for Controllable Text Generation
Zhiting Hu, Li Erran Li
Controllable text generation concerns two fundamental tasks of wide applications, namely generating text of given attributes (i.e., attribute-conditional generation), and minimally…
Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving
Xuanchi Ren, Tao Yang, Li Erran Li +2
Motion prediction of vehicles is critical but challenging due to the uncertainties in complex environments and the limited visibility caused by occlusions and limited sensor ranges…