5 papers
An Empirical Study of Proactive Coding Assistants in Real-World Software Development
Lehui Li, Ruixuan Jia, Guo-Ye Yang +1
Large language model (LLM)-based coding assistants have made substantial progress, yet most systems remain reactive, requiring developers to explicitly formulate their needs. Proac…
AgentExpt: Automating AI Experiment Design with LLM-based Resource Retrieval Agent
Yu Li, Lehui Li, Lin Chen +3
Large language model agents are becoming increasingly capable at web-centric tasks such as information retrieval, complex reasoning. These emerging capabilities have given rise to…
From Text to Forecasts: Bridging Modality Gap with Temporal Evolution Semantic Space
Lehui Li, Yuyao Wang, Jisheng Yan +5
Incorporating textual information into time-series forecasting holds promise for addressing event-driven non-stationarity; however, a fundamental modality gap hinders effective fus…
What Papers Don't Tell You: Recovering Tacit Knowledge for Automated Paper Reproduction
Lehui Li, Ruining Wang, Haochen Song +8
Automated paper reproduction -- generating executable code from academic papers -- is bottlenecked not by information retrieval but by the tacit knowledge that papers inevitably le…
AgentSwift: Efficient LLM Agent Design via Value-guided Hierarchical Search
Yu Li, Lehui Li, Zhihao Wu +5
Large language model (LLM) agents have demonstrated strong capabilities across diverse domains, yet automated agent design remains a significant challenge. Current automated agent…