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Large language models (LLMs) provide powerful means to leverage prior knowledge for predictive modeling when data is limited. In this work, we demonstrate how LLMs can use their compressed world knowledge to generate intrinsically…

Pre-trained large language models (LLMs) have demonstrated strong common-sense reasoning abilities, making them promising for robotic navigation and planning tasks. However, despite recent progress, bridging the gap between language…

机器人学 · 计算机科学 2025-12-29 Mingfeng Yuan , Letian Wang , Steven L. Waslander

Planning represents a fundamental capability of intelligent agents, requiring comprehensive environmental understanding, rigorous logical reasoning, and effective sequential decision-making. While Large Language Models (LLMs) have…

人工智能 · 计算机科学 2025-05-27 Pengfei Cao , Tianyi Men , Wencan Liu , Jingwen Zhang , Xuzhao Li , Xixun Lin , Dianbo Sui , Yanan Cao , Kang Liu , Jun Zhao

Subjective well-being is a key metric in economic, medical, and policy decision-making. As artificial intelligence provides scalable tools for modelling human outcomes, it is crucial to evaluate whether large language models (LLMs) can…

人机交互 · 计算机科学 2025-07-09 Pat Pataranutaporn , Nattavudh Powdthavee , Chayapatr Archiwaranguprok , Pattie Maes

Modern Artificial Intelligence applications show great potential for language-related tasks that rely on next-word prediction. The current generation of Large Language Models (LLMs) have been linked to claims about human-like linguistic…

计算与语言 · 计算机科学 2024-09-05 Evelina Leivada , Gary Marcus , Fritz Günther , Elliot Murphy

The potential for Large Language Models (LLMs) to generate new information offers a potential step change for research and innovation. This is challenging to assert as it can be difficult to determine what an LLM has previously seen during…

计算与语言 · 计算机科学 2024-05-24 Thomas Greatrix , Roger Whitaker , Liam Turner , Walter Colombo

Leveraging large language models (LLMs) for various natural language processing tasks has led to superlative claims about their performance. For the evaluation of machine translation (MT), existing research shows that LLMs are able to…

The advantages of pre-trained large language models (LLMs) are apparent in a variety of language processing tasks. But can a language model's knowledge be further harnessed to effectively disambiguate objects and navigate decision-making…

机器人学 · 计算机科学 2024-01-09 Connie Jiang , Yiqing Xu , David Hsu

In recent years, pre-trained large language models (LLMs) have demonstrated remarkable efficiency in achieving an inference-time few-shot learning capability known as in-context learning. However, existing literature has highlighted the…

计算与语言 · 计算机科学 2024-02-14 Xinyi Wang , Wanrong Zhu , Michael Saxon , Mark Steyvers , William Yang Wang

Large language models (LLMs) are increasingly used to predict human behavior. We propose a measure for evaluating how much knowledge a pretrained LLM brings to such a prediction: its equivalent sample size, defined as the amount of…

计量经济学 · 经济学 2026-01-21 Wayne Gao , Sukjin Han , Annie Liang

As a key advancement in artificial intelligence, large language models (LLMs) are set to transform transportation systems. While LLMs offer the potential to simulate human travelers in future mixed-autonomy transportation systems, their…

综合经济学 · 经济学 2026-02-04 Yingnan Yan , Tianming Liu , Yafeng Yin

Large Language Models (LLMs) offer a promising alternative to traditional survey methods, potentially enhancing efficiency and reducing costs. In this study, we use LLMs to create virtual populations that answer survey questions, enabling…

人机交互 · 计算机科学 2025-03-24 Enzo Sinacola , Arnault Pachot , Thierry Petit

Validating Large Language Models with ReLM explores the application of formal languages to evaluate and control Large Language Models (LLMs) for memorization, bias, and zero-shot performance. Current approaches for evaluating these types…

计算与语言 · 计算机科学 2025-04-18 Reece Adamson , Erin Song

By encoding time series as a string of numerical digits, we can frame time series forecasting as next-token prediction in text. Developing this approach, we find that large language models (LLMs) such as GPT-3 and LLaMA-2 can surprisingly…

机器学习 · 计算机科学 2024-08-13 Nate Gruver , Marc Finzi , Shikai Qiu , Andrew Gordon Wilson

Visual target navigation in unknown environments is a crucial problem in robotics. Despite extensive investigation of classical and learning-based approaches in the past, robots lack common-sense knowledge about household objects and…

机器人学 · 计算机科学 2023-12-27 Bangguo Yu , Hamidreza Kasaei , Ming Cao

Recent advancements in Large Language Models (LLMs) have made them a popular information-seeking tool among end users. However, the statistical training methods for LLMs have raised concerns about their representation of under-represented…

Large language models (LLMs) have exerted a considerable impact on diverse language-related tasks in recent years. Their demonstrated state-of-the-art performance is achieved through methodologies such as zero-shot or few-shot prompting.…

计算与语言 · 计算机科学 2023-12-21 Arshad Kaji , Manan Shah

Large language models (LLMs) have rapidly become familiar tools to researchers and practitioners. Concepts such as prompting, temperature, or few-shot examples are now widely recognized, and LLMs are increasingly used in Modeling &…

人工智能 · 计算机科学 2026-02-06 Philippe J. Giabbanelli

Large Language Models (LLMs) have demonstrated their capabilities across various tasks, from language translation to complex reasoning. Understanding and predicting human behavior and biases are crucial for artificial intelligence (AI)…

人工智能 · 计算机科学 2024-08-06 Thuy Ngoc Nguyen , Kasturi Jamale , Cleotilde Gonzalez

Large language models (LLMs) are increasingly used in statistical research and applications. However,they are also notorious for unreliable or biased information. Here, we explore whether LLMs can be used to improve the precision of…

应用统计 · 统计学 2026-05-29 Jaylin Lowe , Adam Sales , Johann A. Gagnon-Bartsch