8 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…
Uncovering Linguistic Fragility in Vision-Language-Action Models via Diversity-Aware Red Teaming
Baoshun Tong, Haoran He, Ling Pan +2
Vision-Language-Action (VLA) models have achieved remarkable success in robotic manipulation. However, their robustness to linguistic nuances remains a critical, under-explored saf…
GARDO: Reinforcing Diffusion Models without Reward Hacking
Haoran He, Yuxiao Ye, Jie Liu +7
Fine-tuning diffusion models via online reinforcement learning (RL) has shown great potential for enhancing text-to-image alignment. However, since precisely specifying a ground-tr…
Random Policy Valuation is Enough for LLM Reasoning with Verifiable Rewards
Haoran He, Yuxiao Ye, Qingpeng Cai +4
RL with Verifiable Rewards (RLVR) has emerged as a promising paradigm for improving the reasoning abilities of large language models (LLMs). Current methods rely primarily on polic…
Random Policy Evaluation Uncovers Policies of Generative Flow Networks
Haoran He, Emmanuel Bengio, Qingpeng Cai +1
The Generative Flow Network (GFlowNet) is a probabilistic framework in which an agent learns a stochastic policy and flow functions to sample objects proportionally to an unnormali…
Scaling Image and Video Generation via Test-Time Evolutionary Search
Haoran He, Jiajun Liang, Xintao Wang +4
As the marginal cost of scaling computation (data and parameters) during model pre-training continues to increase substantially, test-time scaling (TTS) has emerged as a promising…