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The ability of large language models (LLMs) to mimic human-like intelligence has led to a surge in LLM-based autonomous agents. Though recent LLMs seem capable of planning and reasoning given user instructions, their effectiveness in…

Recent advancements in large language models (LLMs) have revealed their potential for achieving autonomous agents possessing human-level intelligence. However, existing benchmarks for evaluating LLM Agents either use static datasets,…

计算与语言 · 计算机科学 2024-02-27 Junzhe Chen , Xuming Hu , Shuodi Liu , Shiyu Huang , Wei-Wei Tu , Zhaofeng He , Lijie Wen

Recent research explores optimization using large language models (LLMs) by either iteratively seeking next-step solutions from LLMs or directly prompting LLMs for an optimizer. However, these approaches exhibit inherent limitations,…

最优化与控制 · 数学 2024-03-06 Zeyuan Ma , Hongshu Guo , Jiacheng Chen , Guojun Peng , Zhiguang Cao , Yining Ma , Yue-Jiao Gong

In the Vision-and-Language Navigation (VLN) task, the agent is required to navigate to a destination following a natural language instruction. While learning-based approaches have been a major solution to the task, they suffer from high…

人工智能 · 计算机科学 2024-08-13 Zhaohuan Zhan , Lisha Yu , Sijie Yu , Guang Tan

Large Language Models (LLMs) are versatile, yet they often falter in tasks requiring deep and reliable reasoning due to issues like hallucinations, limiting their applicability in critical scenarios. This paper introduces a rigorously…

计算与语言 · 计算机科学 2023-11-21 Saizhuo Wang , Zhihan Liu , Zhaoran Wang , Jian Guo

Uncrewed Aerial Vehicles (UAVs) are widely deployed across diverse applications due to their mobility and agility. Recent advances in Large Language Models (LLMs) offer a transformative opportunity to enhance UAV intelligence beyond…

机器人学 · 计算机科学 2026-03-03 Yousef Emami , Hao Zhou , Radha Reddy , Atefeh Hajijamali Arani , Biliang Wang , Kai Li , Luis Almeida , Zhu Han

Although large language models (LLMs) are introduced into vision-and-language navigation (VLN) to improve instruction comprehension and generalization, existing LLM- based VLN lacks the ability to selectively recall and use relevant priori…

人工智能 · 计算机科学 2026-03-10 Haozhou Li , Xiangyu Dong , Huiyan Jiang , Yaoming Zhou , Xiaoguang Ma

The emergence of Large Language Models (LLMs) has revolutionized natural language processing in various applications especially in e-commerce. One crucial step before the application of such LLMs in these fields is to understand and compare…

计算与语言 · 计算机科学 2024-08-26 Chester Palen-Michel , Ruixiang Wang , Yipeng Zhang , David Yu , Canran Xu , Zhe Wu

Large Language Models (LLMs) have recently emerged as a focal point of research and application, driven by their unprecedented ability to understand and generate text with human-like quality. Even more recently, LLMs have been extended into…

计算与语言 · 计算机科学 2024-04-03 Kilian Carolan , Laura Fennelly , Alan F. Smeaton

Enabling robotic assistants to navigate complex environments and locate objects described in free-form language is a critical capability for real-world deployment. While foundation models, particularly Vision-Language Models (VLMs), offer…

机器人学 · 计算机科学 2026-04-16 Naoki Yokoyama , Sehoon Ha

Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have made them powerful tools in embodied navigation, enabling agents to leverage commonsense and spatial reasoning for efficient exploration in…

A Language Model is a term that encompasses various types of models designed to understand and generate human communication. Large Language Models (LLMs) have gained significant attention due to their ability to process text with human-like…

Large multimodal models (LMMs) show strong visual-linguistic reasoning but their capacity for spatial decision-making and action remains unclear. In this work, we investigate whether LMMs can achieve embodied spatial action like human…

Large language models (LLMs) have demonstrated strong performance in general-purpose machine translation, but their effectiveness in complex, domain-sensitive translation tasks remains underexplored. Recent advancements in Large Reasoning…

计算与语言 · 计算机科学 2025-05-27 Yongshi Ye , Biao Fu , Chongxuan Huang , Yidong Chen , Xiaodong Shi

Large Language Models (LLMs) have demonstrated remarkable potential in advancing scientific knowledge and addressing complex challenges. In this work, we introduce OmniScience, a specialized large reasoning model for general science,…

Large language models (LLMs) have exhibited remarkable capabilities across various domains and tasks, pushing the boundaries of our knowledge in learning and cognition. The latest model, OpenAI's o1, stands out as the first LLM with an…

计算与语言 · 计算机科学 2024-09-24 Yunfei Xie , Juncheng Wu , Haoqin Tu , Siwei Yang , Bingchen Zhao , Yongshuo Zong , Qiao Jin , Cihang Xie , Yuyin Zhou

In the field of robotics and automation, navigation systems based on Large Language Models (LLMs) have recently demonstrated impressive performance. However, the security aspects of these systems have received relatively less attention.…

Recent advancements in Large Reasoning Models (LRMs), such as OpenAI's o1/o3 and DeepSeek-R1, have demonstrated remarkable performance in specialized reasoning tasks through human-like deliberative thinking and long chain-of-thought…

人工智能 · 计算机科学 2025-11-20 Weixiang Zhao , Xingyu Sui , Jiahe Guo , Yulin Hu , Yang Deng , Yanyan Zhao , Xuda Zhi , Yongbo Huang , Hao He , Wanxiang Che , Ting Liu , Bing Qin

Large Language Models (LLMs) have the potential to semi-automate some process mining (PM) analyses. While commercial models are already adequate for many analytics tasks, the competitive level of open-source LLMs in PM tasks is unknown. In…

计算与语言 · 计算机科学 2024-07-19 Alessandro Berti , Humam Kourani , Wil M. P. van der Aalst

Context: Large Language Models (LLMs) enable automation of complex natural language processing across domains, but research on domain-specific applications like Finance remains limited. Objectives: This study explored open-source and…

软件工程 · 计算机科学 2025-09-30 Theo Koraag , Niklas Wagner , Felix Dobslaw , Lucas Gren