Many real-world tasks (e.g., office workflows, scientific experimentation) require LLM agents to interact repeatedly with their environments for context-dependent operations. However, such environments are often not agent-ready. First, information is often scattered and fragmented across the environment. Second, releva...
Yu-Kai Wu, Yuan-Jing Yang, Leon Zhou et al.· 0 citations
Env-Rethink is proposed, a system with 27B post-trained model that supports three main capabilities that adaptively builds Collection Maps and Event Logs to supplement necessary context and evolves environments through virtual event histories that alter environmental states and evidence relationships.
Yu-Kai Wu, Yuan-Jing Yang, Leon Zhou et al.· 0 citations
General-purpose AI document assistants (e.g., NotebookLM) increasingly play an important role and are widely adopted across diverse domains. However, they consistently struggle on complicated multimodal documents such as financial reports and scientific papers, where hierarchical structures, complex layouts, and interl...
Yu-Kai Wu, Bang-Rui Xu, Shao-Lin Yu et al.· Proceedings of the VLDB Endo...· 0 citations
OmniOpt supplies the research community with an operational coordinate system for selecting optimizers under explicit mechanism and objective assumptions, and charts a direction for the future development of the optimizer community.
Siyuan Li, Jiabao Pan, Yumou Liu et al.· 0 citations
Results show that a fixed-weight, self-evolving harness can revise, recover, and accumulate verified approaches while producing structured trajectories for future supervised and reinforcement learning.
Boxiu Li, Zi-Mo Wen, Yi-Jia Fan et al.· 2 citations· ⚡1
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
