Chenyuan Zhang

Unearthing two distinct planning competencies in LLMs reveals that scaling up models enhances operational reasoning but leaves structural enumeration largely unchanged.

Urban facade reconstruction can achieve superior geometric accuracy by integrating lightweight structural supervision, overcoming common pitfalls of traditional methods.

Reasoning across languages doesn't have to break the bank: a new framework slashes token costs by over 50% while maintaining accuracy, especially boosting performance in low-resource languages.