10 papers
Tree-of-Experience: Hierarchical Experience Management for Self-Evolving Agents
Zihao Deng, Yining Zhu, Leiming Wang +6
Continual self-evolution requires LLM agents to transform environmental interactions into reliable and reusable experience. Existing methods typically refine individual trajectorie…
FinEvolveBench: A Benchmark for Self-Evolving Agents on Low-Repetition Tasks with Implicit Rewards
Zihao Deng, Yining Zhu, Leiming Wang +6
Experience-based self-evolution enables language-model agents to improve their behavior by accumulating and updating experience at test time, yet existing evaluations often assume…
Inference-Time Alignment of Diffusion Models via Trust-Region Iterative Twisted Sequential Monte Carlo
Weixin Wang, Yu Yang, Wei Deng +1
We study inference-time alignment for diffusion-based generative models, aiming to steer a base model toward high-reward outputs without updating its weights. Recent Sequential Mon…
Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning
Yu Yang, Yihong Guo, Anqi Liu +1
Off-dynamics offline reinforcement learning seeks to learn a target-domain policy from a large source dataset and a limited target dataset under mismatched transition dynamics. Exi…
SPIKE: An Adaptive Dual Controller Framework for Cost-Efficient Long-Horizon Game Agents
Wencan Jiang, Jiangning Zhang, Jianbiao Mei +6
Long-horizon multimodal agents in open-world games must stay goal-directed across many low-level interactions under tight token and latency budgets. Existing approaches often trade…
MOBODY: Model Based Off-Dynamics Offline Reinforcement Learning
Yihong Guo, Yu Yang, Pan Xu +1
We study off-dynamics offline reinforcement learning, where the goal is to learn a policy from offline source and limited target datasets with mismatched dynamics. Existing methods…