MOA: Multi-Objective Alignment for Role-Playing Agents Paper • 2512.09756 • Published 19 days ago • 3
MOA: Multi-Objective Alignment for Role-Playing Agents Paper • 2512.09756 • Published 19 days ago • 3
Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints Paper • 2510.08549 • Published Oct 9 • 6
Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints Paper • 2510.08549 • Published Oct 9 • 6
Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints Paper • 2510.08549 • Published Oct 9 • 6 • 2
Thought-Augmented Policy Optimization: Bridging External Guidance and Internal Capabilities Paper • 2505.15692 • Published May 21 • 14
Thought-Augmented Policy Optimization: Bridging External Guidance and Internal Capabilities Paper • 2505.15692 • Published May 21 • 14
Vid2World: Crafting Video Diffusion Models to Interactive World Models Paper • 2505.14357 • Published May 20 • 27
Self-Generated In-Context Examples Improve LLM Agents for Sequential Decision-Making Tasks Paper • 2505.00234 • Published May 1 • 26
WORLDMEM: Long-term Consistent World Simulation with Memory Paper • 2504.12369 • Published Apr 16 • 35
WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents Paper • 2504.15785 • Published Apr 22 • 22