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相关论文: Can LLMs plan paths in the real world?

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With the rapid development of online services, recommender systems (RS) have become increasingly indispensable for mitigating information overload. Despite remarkable progress, conventional recommendation models (CRM) still have some…

There is a rapidly growing number of open-source Large Language Models (LLMs) and benchmark datasets to compare them. While some models dominate these benchmarks, no single model typically achieves the best accuracy in all tasks and use…

计算与语言 · 计算机科学 2023-09-28 Tal Shnitzer , Anthony Ou , Mírian Silva , Kate Soule , Yuekai Sun , Justin Solomon , Neil Thompson , Mikhail Yurochkin

Large language models (LLMs) exhibit advanced reasoning skills, enabling robots to comprehend natural language instructions and strategically plan high-level actions through proper grounding. However, LLM hallucination may result in robots…

人工智能 · 计算机科学 2025-02-12 Kaiqu Liang , Zixu Zhang , Jaime Fernández Fisac

Interest in the role of large language models (LLMs) in education is increasing, considering the new opportunities they offer for teaching, learning, and assessment. In this paper, we examine the impact of LLMs on educational NLP in the…

计算与语言 · 计算机科学 2026-01-19 Sowmya Vajjala , Bashar Alhafni , Stefano Bannò , Kaushal Kumar Maurya , Ekaterina Kochmar

The widespread adoption of Large Language Models (LLMs) has become commonplace, particularly with the emergence of open-source models. More importantly, smaller models are well-suited for integration into consumer devices and are frequently…

计算与语言 · 计算机科学 2024-08-16 Aisha Khatun , Daniel G. Brown

Studying the robustness of Large Language Models (LLMs) to unsafe behaviors is an important topic of research today. Building safety classification models or guard models, which are fine-tuned models for input/output safety classification…

计算与语言 · 计算机科学 2025-07-30 Sowmya Vajjala

This study examines the feasibility of applying large language models (LLMs) for forecasting the impact of traffic incidents on the traffic flow. The use of LLMs for this task has several advantages over existing machine learning-based…

人工智能 · 计算机科学 2025-07-08 George Jagadeesh , Srikrishna Iyer , Michal Polanowski , Kai Xin Thia

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

The introduction of large language models (LLMs) has greatly enhanced the capabilities of software agents. Instead of relying on rule-based interactions, agents can now interact in flexible ways akin to humans. However, this flexibility…

Large language models (LLMs) represent significant breakthroughs in artificial intelligence and hold potential for applications within smart grids. However, as demonstrated in previous literature, AI technologies are susceptible to various…

密码学与安全 · 计算机科学 2025-04-22 Jiangnan Li , Yingyuan Yang , Jinyuan Sun

ChatGPT embarks on a new era of artificial intelligence and will revolutionize the way we approach intelligent traffic safety systems. This paper begins with a brief introduction about the development of large language models (LLMs). Next,…

计算与语言 · 计算机科学 2023-09-07 Ou Zheng , Mohamed Abdel-Aty , Dongdong Wang , Zijin Wang , Shengxuan Ding

Large language models (LLMs) have become essential tools in software development, widely used for requirements engineering, code generation and review tasks. Software engineers often rely on LLMs to verify if code implementation satisfy…

软件工程 · 计算机科学 2026-03-03 Haolin Jin , Huaming Chen

Large language models (LLMs) are being increasingly incorporated into scientific workflows. However, we have yet to fully grasp the implications of this integration. How should the advent of large language models affect the practice of…

Recent developments in large language models (LLMs) have unlocked new opportunities for healthcare, from information synthesis to clinical decision support. These new LLMs are not just capable of modeling language, but can also act as…

The paper underscores the significance of Large Language Models (LLMs) in reshaping recommender systems, attributing their value to unique reasoning abilities absent in traditional recommenders. Unlike conventional systems lacking direct…

信息检索 · 计算机科学 2024-03-20 Arpita Vats , Vinija Jain , Rahul Raja , Aman Chadha

Recent advancements in integrating large language models (LLMs) with tools have allowed the models to interact with real-world environments. However, these tool-augmented LLMs often encounter incomplete scenarios when users provide partial…

计算与语言 · 计算机科学 2025-08-05 Seungbin Yang , ChaeHun Park , Taehee Kim , Jaegul Choo

Large Language Models (LLMs) went from non-existent to ubiquitous in the machine learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify the remaining challenges and already fruitful application…

计算与语言 · 计算机科学 2023-07-20 Jean Kaddour , Joshua Harris , Maximilian Mozes , Herbie Bradley , Roberta Raileanu , Robert McHardy

The language generation and reasoning capabilities of large language models (LLMs) have enabled conversational systems with impressive performance in a variety of tasks, from code generation, to composing essays, to passing STEM and legal…

人工智能 · 计算机科学 2025-02-28 Konstantina Christakopoulou , Iris Qu , John Canny , Andrew Goodridge , Cj Adams , Minmin Chen , Maja Matarić

Large language models (LLMs) are increasingly being adopted in high-stakes domains. Their potential to encode evolving social contexts and to generate plausible scenarios position them as promising tools in social policymaking. This article…

人工智能 · 计算机科学 2026-01-30 Pierre Le Coz , Jia An Liu , Debarun Bhattacharjya , Georgina Curto , Serge Stinckwich

Large Language Models (LLMs) are increasingly consulted for high-stakes life advice, yet they lack standard safeguards against providing confident but misguided responses. This creates risks of sycophancy and over-confidence. This paper…

人工智能 · 计算机科学 2025-07-30 Joshua Adrian Cahyono , Saran Subramanian
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