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Large language models (LLMs) have unlocked new capabilities of task planning from human instructions. However, prior attempts to apply LLMs to real-world robotic tasks are limited by the lack of grounding in the surrounding scene. In this…

Effective planning is essential for the success of any task, from organizing a vacation to routing autonomous vehicles and developing corporate strategies. It involves setting goals, formulating plans, and allocating resources to achieve…

人工智能 · 计算机科学 2024-09-04 Haoming Li , Zhaoliang Chen , Jonathan Zhang , Fei Liu

This paper introduces an approach to increasing the explainability of artificial intelligence (AI) systems by embedding Large Language Models (LLMs) within standardized analytical processes. While traditional explainable AI (XAI) methods…

人工智能 · 计算机科学 2025-11-11 Marc Jansen , Marcel Pehlke

Large language models (LLMs) have not only revolutionized the field of natural language processing (NLP) but also have the potential to bring a paradigm shift in many other fields due to their remarkable abilities of language understanding,…

信息检索 · 计算机科学 2024-10-29 Qi Wang , Jindong Li , Shiqi Wang , Qianli Xing , Runliang Niu , He Kong , Rui Li , Guodong Long , Yi Chang , Chengqi Zhang

In recent years, multi-agent frameworks powered by large language models (LLMs) have advanced rapidly. Despite this progress, there is still a notable absence of benchmark datasets specifically tailored to evaluate their performance. To…

计算与语言 · 计算机科学 2025-04-28 Lei Shen , Xiaoyu Shen

Large Language Models (LLMs) have become increasingly capable of handling diverse tasks with the aid of well-crafted prompts and integration of external tools, but as task complexity rises, the workflow involving LLMs can be complicated and…

人工智能 · 计算机科学 2024-06-21 Honghua Dong , Qidong Su , Yubo Gao , Zhaoyu Li , Yangjun Ruan , Gennady Pekhimenko , Chris J. Maddison , Xujie Si

Intelligent Process Automation (IPA) is an emerging technology with a primary goal to assist the knowledge worker by taking care of repetitive, routine and low-cognitive tasks. Conversational agents that can interact with users in a natural…

计算与语言 · 计算机科学 2020-05-22 Alena Moiseeva , Dietrich Trautmann , Michael Heimann , Hinrich Schütze

Simulations, although powerful in accurately replicating real-world systems, often remain inaccessible to non-technical users due to their complexity. Conversely, large language models (LLMs) provide intuitive, language-based interactions…

计算与语言 · 计算机科学 2025-05-22 Jacob Kleiman , Kevin Frank , Joseph Voyles , Sindy Campagna

AI-assisted decision making becomes increasingly prevalent, yet individuals often fail to utilize AI-based decision aids appropriately especially when the AI explanations are absent, potentially as they do not %understand reflect on AI's…

人机交互 · 计算机科学 2025-02-18 Zhuoyan Li , Hangxiao Zhu , Zhuoran Lu , Ziang Xiao , Ming Yin

Since the explosion in popularity of ChatGPT, large language models (LLMs) have continued to impact our everyday lives. Equipped with external tools that are designed for a specific purpose (e.g., for flight booking or an alarm clock), LLM…

人机交互 · 计算机科学 2025-02-04 Gaole He , Gianluca Demartini , Ujwal Gadiraju

Inspired by the exceptional general intelligence of Large Language Models (LLMs), researchers have begun to explore their application in pioneering the next generation of recommender systems - systems that are conversational, explainable,…

信息检索 · 计算机科学 2024-08-06 Wensheng Lu , Jianxun Lian , Wei Zhang , Guanghua Li , Mingyang Zhou , Hao Liao , Xing Xie

Large Language Models (LLMs) are increasingly used to build autonomous agents that perform complex tasks with external tools, often exposed through APIs in enterprise systems. Direct use of these APIs is difficult due to the complex input…

Large Language Models (LLMs) have made significant strides in various intelligent tasks but still struggle with complex action reasoning tasks that require systematic search. To address this limitation, we propose a method that bridges the…

计算与语言 · 计算机科学 2025-02-05 Adam Ishay , Joohyung Lee

Large Language Models (LLMs) have emerged as a promising alternative to traditional static program analysis methods, such as symbolic execution, offering the ability to reason over code directly without relying on theorem provers or SMT…

编程语言 · 计算机科学 2025-09-22 Yihe Li , Ruijie Meng , Gregory J. Duck

Executing computer programs described in natural language has long been a pursuit of computer science. With the advent of enhanced natural language understanding capabilities exhibited by large language models (LLMs), the path toward this…

计算与语言 · 计算机科学 2024-03-15 Xin Zheng , Qiming Zhu , Hongyu Lin , Yaojie Lu , Xianpei Han , Le Sun

This paper introduces LLM-MARS, first technology that utilizes a Large Language Model based Artificial Intelligence for Multi-Agent Robot Systems. LLM-MARS enables dynamic dialogues between humans and robots, allowing the latter to generate…

Augmenting large language models (LLMs) with external tools has emerged as a promising approach to extend their utility, enabling them to solve practical tasks. Previous methods manually parse tool documentation and create in-context…

计算与语言 · 计算机科学 2025-03-05 Zhengliang Shi , Shen Gao , Lingyong Yan , Yue Feng , Xiuyi Chen , Zhumin Chen , Dawei Yin , Suzan Verberne , Zhaochun Ren

Web agents powered by Large Language Models (LLMs) have demonstrated remarkable abilities in planning and executing multi-step interactions within complex web-based environments, fulfilling a wide range of web navigation tasks. Despite…

计算与语言 · 计算机科学 2024-02-26 Yang Deng , Xuan Zhang , Wenxuan Zhang , Yifei Yuan , See-Kiong Ng , Tat-Seng Chua

Video procedure planning, i.e., planning a sequence of action steps given the video frames of start and goal states, is an essential ability for embodied AI. Recent works utilize Large Language Models (LLMs) to generate enriched action step…

计算机视觉与模式识别 · 计算机科学 2025-01-08 Dejie Yang , Zijing Zhao , Yang Liu

Developing autonomous agents for web-based tasks is a core challenge in AI. While Large Language Model (LLM) agents can interpret complex user requests, they often operate as black boxes, making it difficult to diagnose why they fail or how…

人工智能 · 计算机科学 2026-03-16 Orit Shahnovsky , Rotem Dror