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Found 5 papers, 0 papers with code
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions
The remarkable performance of large language models (LLMs) in content generation, coding, and common-sense reasoning has spurred widespread integration into many facets of society.
Diffusion Policy Policy Optimization
We introduce Diffusion Policy Policy Optimization, DPPO, an algorithmic framework including best practices for fine-tuning diffusion-based policies (e. g. Diffusion Policy) in continuous control and robot learning tasks using the policy gradient (PG) method from reinforcement learning (RL).
Blending Data-Driven Priors in Dynamic Games
We formulate KLGame, an algorithm for solving non-cooperative dynamic game with Kullback-Leibler (KL) regularization with respect to a general, stochastic, and possibly multi-modal reference policy.
NashFormer: Leveraging Local Nash Equilibria for Semantically Diverse Trajectory Prediction
Interactions between road agents present a significant challenge in trajectory prediction, especially in cases involving multiple agents.
Provably Efficient Multi-Agent Reinforcement Learning with Fully Decentralized Communication
Distributed exploration reduces sampling complexity in multi-agent RL (MARL).
