Closed-source agents suffer from several issues such as a lack of affordability, transparency,
and reproducibility, particularly on complex interactive tasks. This motivates the …

We introduce Lumos, a novel framework for training language agents that employs a unified
data format and a modular architecture based on open-source large language models …

Recent advancements in Large Language Models (LLMs) showcase advanced reasoning,
yet NLP evaluations often depend on static benchmarks. Evaluating this necessitates …

Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …

Large Language Models (LLMs) have demonstrated impressive capability in many natural
language tasks. However, the auto-regressive generation process makes LLMs prone to …

Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …

The ability to plan a course of action that achieves a desired state of affairs has long been
considered a core competence of intelligent agents and has been an integral part of AI …

The building sector is a significant energy consumer, making building energy optimization
crucial for reducing energy demand. Automating energy optimization tasks eases the …

Recent advancements in Large Language Models (LLMs) have shown significant progress
in understanding complex natural language. One important application of LLM is LLM-based …

Generative models are a class of AI models capable of creating new instances of data by
learning and sampling from their statistical distributions. In recent years, these models have …