10 papers
Beyond Explicit Intent: Discovering and Shaping Artistic Intent through Human-AI Co-Creation
Renye Yan, Jialun Zhong, Jikang Cheng +3
Generative AI is becoming an important medium for artistic creation, yet existing interactions often assume that creators can specify intentions in advance and accurately communica…
VIEWCRAFT: Evolving What Multimodal Agents See and How They Read It
Binxiao Xu, Ruichuan An, Bocheng Zou +7
Reusable skills improve multimodal agents without updating model weights, but their effectiveness depends on both the evidence presented and the procedure used to read it. We intro…
Can We Perform Online RL for Image Editing without Editing Rewards?
Qichao Ma, Jikang Cheng, Ling Liang +3
Reinforcement learning (RL) enables direct preference optimization for image editing through editing-specific rewards, which remain less developed due to costly triplet supervision…
VideoCoCo: Code-as-CoT for Physically-Consistent Video Generation via an Agentic Dual-Engine System
Haodong Li, Tianfei Ren, Xiaoxiao Ma +25
Text-to-video models have achieved remarkable visual quality, yet they still struggle to generate physically consistent dynamics because the temporal evolution of a scene must be i…
GenTrack: Physical Alignment for Robot-Native Motion Generation and Zero-Shot Humanoid Tracking
Zeyu Ling, Xinyao Yu, Renye Yan +4
General-purpose humanoid trackers can execute diverse references, but their zero-shot coverage depends on large embodied corpora that are costly to extend. Text-to-motion generator…
AdaMemento: Adaptive Memory-Assisted Policy Optimization for Reinforcement Learning
Renye Yan, Yaozhong Gan, You Wu +4
In sparse reward scenarios of reinforcement learning (RL), the memory mechanism provides promising shortcuts to policy optimization by reflecting on past experiences like humans. H…
Inner-Probe: Discovering Copyright-related Data Generation in LLM Architecture
Qichao Ma, Rui-Jie Zhu, Peiye Liu +8
Large Language Models (LLMs) utilize extensive knowledge databases and show powerful text generation ability. However, their reliance on high-quality copyrighted datasets raises co…
The Exploration-Exploitation Dilemma Revisited: An Entropy Perspective
Renye Yan, Yaozhong Gan, You Wu +4
The imbalance of exploration and exploitation has long been a significant challenge in reinforcement learning. In policy optimization, excessive reliance on exploration reduces lea…
Transductive Off-policy Proximal Policy Optimization
Yaozhong Gan, Renye Yan, Xiaoyang Tan +2
Proximal Policy Optimization (PPO) is a popular model-free reinforcement learning algorithm, esteemed for its simplicity and efficacy. However, due to its inherent on-policy nature…
Reflective Policy Optimization
Yaozhong Gan, Renye Yan, Zhe Wu +1
On-policy reinforcement learning methods, like Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO), often demand extensive data per update, leading to sa…