Data refinement involves executing multi-step recipes over evolving text states, where both composition and execution order of processing operators determine the outcome. While existing benchmarks either isolate text editing or entangle it with code and tool execution, it remains…
Online reinforcement learning is widely used to align large language models (LLMs) with reward signals, yet training can be unstable under noisy or misspecified rewards. We identify a failure mode we call directional inconsistency: within a batch, a small set of high-reward rollo…
The rapid adoption of electric vehicles (EVs) has driven a strong need for optimizing locations of electric vehicle charging stations (EVCSs). Previous methods for locating EVCSs rely on statistical and optimization models, but these methods have limitations in capturing complex…