Large Language Models (LLMs) are poised to play an increasingly important role in our lives, providing assistance across a wide array of tasks. In the geospatial domain, LLMs have demonstrated the ability to answer generic questions, such as identifying a country's capital; nonetheless, their utility is hindered when it comes to answering fine-grained questions about specific places, such as grocery stores or restaurants, which constitute essential aspects of people's everyday lives. This is mainly because the places in our cities haven't been systematically fed into LLMs, so as to understand and memorize them. This study introduces a novel framework for fine-tuning a pre-trained model on city-specific data, to enable it to provide accurate recommendations, while minimizing hallucinations. We share our model, LAMP, and the data used to train it. We conduct experiments to analyze its ability to correctly retrieving spatial objects, and compare it to well-known open- and closed- source language models, such as GPT-4. Finally, we explore its emerging capabilities through a case study on day planning.
LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification
Tsinghua Shenzhen International Graduate School, Tsinghua University（清华大学清华大学深圳国际研究生院）；School of Automation, Wuhan University of Technology（武汉理工大学自动化学院）
LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs
Purdue University（普渡大学）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of Virginia（弗吉尼亚大学）；InfoTech Labs, Toyota Motor North America（丰田北美信息技术实验室）
Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学人工智能学院 Gallagher 学院）；Engineering Research Center of Next-Generation Intelligent Search and Recommendation, MOE（下一代智能搜索与推荐工程研究中心，教育部）；Baidu Inc.（百度公司）
LLM4AD: Large Language Models for Autonomous Driving -- Concept, Review, Benchmark, Experiments, and Future Trends
Purdue University（普渡大学）；Institute for Physical Artificial Intelligence (IPAI), Purdue University（普渡大学物理人工智能研究所）；Department of Computer Science, Purdue University（普渡大学计算机科学系）；InfoTech Labs, Toyota Motor North America（丰田北美信息技术实验室）
