3 papers
cs.LG2026
EEVEE: Towards Test-time Prompt Learning in the Real World for Self-Improving Agents
Weixian Xu, Shilong Liu, Mengdi Wang
In this paper, we propose EEVEE, the first multi-dataset test-time prompt learning framework for LLM agents, enabling test-time prompt learning under real-world task streams. Exist…
cs.AI2026
ASI-Evolve: AI Accelerates AI
Weixian Xu, Tiantian Mi, Yixiu Liu +6
Can AI accelerate the development of AI itself? While recent agentic systems have shown strong performance on well-scoped tasks with rapid feedback, it remains unclear whether they…
cs.RO2025
HBTP: Heuristic Behavior Tree Planning with Large Language Model Reasoning
Yishuai Cai, Xinglin Chen, Yunxin Mao +4
Behavior Trees (BTs) are increasingly becoming a popular control structure in robotics due to their modularity, reactivity, and robustness. In terms of BT generation methods, BT pl…