Environment-aware Model Selection (EMS), an adaptive VLA inference framework that switches between two fully decoupled systems of different scales through environment-aware model selection, and offers three key advantages over prior hierarchical VLA frameworks: a fully decoupled and modular dual-system architecture tha...
Yuewei Sun, Lang Qin, Zechuan Tian et al.· 0 citations
Lifelong LLM agents increasingly adapt through external learning states that store past interactions as retrievable memories or reusable skills, yet existing benchmarks rarely account for how the path of accumulated experience shapes what agents transfer and retain. In this work, we establish PATH-Bench, a benchmark fo...
Xi-Dong Yang, Xing-Yi Zhang, Wen-Hao Li et al.· 0 citations
Apodex 1.1 reaches the leading performance band despite using a substantially smaller model than many frontier systems, and the 35B-parameter Apodex 1.1 Mini further retains strong working capability in a locally deployable form.
General-purpose language models can reason and synthesize knowledge, but complex work also requires sustained interaction with files, information sources, and executable code, together with state maintenance, failure recovery, and verifiable delivery. We call this \emph{working capability}: sustained, verifiable progre...
Apodex Team B. An, B. Li, B. Wang et al.· 0 citations
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