Realistic environment replicas are increasingly valuable for training and evaluating LLM agents, yet the original systems may be inaccessible or impractical to reproduce. We explore agentic language world modeling: rather than rebuilding an executable environment, a world model agent serves as the environment for a tas...
Quan-Yu Long, Xiao Chen, Jian-Da Chen et al.· 0 citations
Memory has become integral to the LLM agent ecosystem, supporting information retention and reuse across interactions. However, most existing agent memory systems construct memory in a query-agnostic manner, which can incur unnecessary preprocessing cost and discard details that later prove essential. Recent studies ha...
Haozhen Zhang, Hao-Dong Yue, Quan-Yu Long et al.· 0 citations
This work presents a unified formulation of LLM routing as a sequential decision process characterized by five components: context encoders, model encoders, scoring functions, decision rules, and learning signals, covering single-turn, multi-turn, and personalized routing.
Tao Feng, Fangxu Yu, Haozhen Zhang et al.· 1 citation
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