3 citations · 3 across the 6 of their papers we have counts for
6 papers
Edit-R2: Context-Aware Reinforcement Learning for Multi-Turn Image Editing
Yuxiao Ye, Haoran He, Fangyuan Kong +4
Text-guided image editing has advanced rapidly with diffusion models and unified multimodal foundation models. However, most existing methods remain confined to single-turn setting…
RedTopic: Toward Topic-Diverse Red Teaming of Large Language Models
Jiale Ding, Xiang Zheng, Yutao Wu +5
As large language models (LLMs) are increasingly deployed as black-box components in real-world applications, red teaming has become essential for identifying potential risks. It t…
Safety challenges of AI in medicine in the era of large language models
Xiaoye Wang, Nicole Xi Zhang, Hongyu He +9
Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs), have unlocked significant potential to enhance the quality and efficiency of medi…
Bifurcated Generative Flow Networks
Chunhui Li, Cheng-Hao Liu, Dianbo Liu +2
Generative Flow Networks (GFlowNets), a new family of probabilistic samplers, have recently emerged as a promising framework for learning stochastic policies that generate high-qua…
Evolution Guided Generative Flow Networks
Zarif Ikram, Ling Pan, Dianbo Liu
Generative Flow Networks (GFlowNets) are a family of probabilistic generative models that learn to sample compositional objects proportional to their rewards. One big challenge of…
Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries
Zarif Ikram, Ling Pan, Dianbo Liu
Due to limited resources and fast economic growth, designing optimal transportation road networks with traffic simulation and validation in a cost-effective manner is vital for dev…