28 papers
Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design
Qing Zong, Jiayu Liu, Junhao Shen +9
Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, such as fixed tasks and feedb…
Long-Horizon Embodied Decision-Making via Multimodal Memory Compression
Bingxuan Li, Rui Yang, Cheng Qian +6
Agents are increasingly expected to act not only as task executors, but also as decision-makers on behalf of human users. This shift requires agents to accumulate evidence over lon…
Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning
Shujin Wu, Cheng Qian, Xiusi Chen +1
Test-time scaling through iterative self-evolution with environment feedback, as demonstrated by AlphaEvolve, shows remarkable performance gains. We hypothesize that the success of…
AdaPlanBench: Evaluating Adaptive Planning in Large Language Model Agents under World and User Constraints
Jiayu Liu, Cheng Qian, Zhenhailong Wang +10
Planning for real-world problems by language models often involves both world and user constraints, which may not be fully specified upfront and are progressively disclosed through…
Trimming the Long-Tail of Visual World Modeling Evaluation
Bingxuan Li, Yining Hong, Cheng Qian +6
Physical interactions follow a long-tailed distribution: a set of common and regular interactions dominates human experience and visual data, while a broad spectrum of rare and irr…
PEARL: Self-Evolving Assistant for Time Management with Reinforcement Learning
Bingxuan Li, Jeonghwan Kim, Cheng Qian +4
Overlapping calendar invitations force busy professionals to repeatedly decide which meetings to attend, reschedule, or decline. We refer to this preference-driven decision process…