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Yuxuan Lu

Northeastern University

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#artificial intelligence Preprint Oct 2026

MiniCorp: The Last Mile of the AI Agent Firm

The last mile toward enterprise AGI is a company that runs itself. Training and adapting such agents require longitudinal enterprise data, which remain scarce, costly to acquire, and often restricted by privacy constraints. Historical archives are also frequently incomplete and record only what actually happened. They...

Jing-Ying Zeng, Zhen-Wei Dai, Jin-Ning Li et al. · 0 citations
Preprint Aug 2026

Retry, Switch, or Abstain? Learning Strategy-Aware Tool-Use Policies via Controlled Error Injection

Tool-using LLM agents are commonly trained and evaluated in environments where tool calls succeed reliably, yet deployed tools can fail transiently, persistently, or silently. Robust recovery therefore requires more than repeated retries: an agent may need to retry the same path, switch to an alternative, or recognize...

Chao-Ran Chen, Vylinh J. Nguyen, Zi-Ji Zhang et al. · 2 citations
Preprint Aug 2026

FactorDrive: Adaptive Multi-Step Reasoning Driven by Planning-Critical Factors for End-to-End Autonomous Driving

FactorDrive is proposed, an end-to-end autonomous driving framework for adaptive multi-step reasoning driven by planning-critical factors (PCFs) and Quality Search-Guided Group Relative Policy Optimization (QS-GRPO), which guides Monte Carlo Tree Search with trajectory-level planning rewards to discover reasoning paths...

Guolei Huang, Tengfei She, Yuxuan Lu et al. · 0 citations

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