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Large Language Models (LLMs) have shown remarkable capabilities in natural language processing, mathematical problem solving, and tasks related to program synthesis. However, their effectiveness in long-term planning and higher-order…

Artificial Intelligence · Computer Science 2024-10-08 Erik Wu , Sayan Mitra

Large language models (LLMs) have demonstrated remarkable zero-shot generalization abilities: state-of-the-art chatbots can provide plausible answers to many common questions that arise in daily life. However, so far, LLMs cannot reliably…

Artificial Intelligence · Computer Science 2023-09-28 Bo Liu , Yuqian Jiang , Xiaohan Zhang , Qiang Liu , Shiqi Zhang , Joydeep Biswas , Peter Stone

Large language models (LLMs) are the result of a massive experiment in bottom-up, data-driven reverse engineering of language at scale. Despite their utility in a number of downstream NLP tasks, ample research has shown that LLMs are…

Artificial Intelligence · Computer Science 2024-08-05 Walid S. Saba

Large Language Models (LLMs) have succeeded remarkably in various natural language processing (NLP) tasks, yet their reasoning capabilities remain a fundamental challenge. While LLMs exhibit impressive fluency and factual recall, their…

Computation and Language · Computer Science 2025-05-29 Avinash Patil , Aryan Jadon

This paper investigates the capabilities of large language models (LLMs) in formulating and solving decision-making problems using mathematical programming. We first conduct a systematic review and meta-analysis of recent literature to…

Artificial Intelligence · Computer Science 2025-08-26 Mohammad J. Abdel-Rahman , Yasmeen Alslman , Dania Refai , Amro Saleh , Malik A. Abu Loha , Mohammad Yahya Hamed

Intrigued by the claims of emergent reasoning capabilities in LLMs trained on general web corpora, in this paper, we set out to investigate their planning capabilities. We aim to evaluate (1) the effectiveness of LLMs in generating plans…

Artificial Intelligence · Computer Science 2023-11-27 Karthik Valmeekam , Matthew Marquez , Sarath Sreedharan , Subbarao Kambhampati

Classical planners are powerful systems, but modeling tasks in input formats such as PDDL is tedious and error-prone. In contrast, planning with Large Language Models (LLMs) allows for almost any input text, but offers no guarantees on plan…

Artificial Intelligence · Computer Science 2025-10-02 Elliot Gestrin , Marco Kuhlmann , Jendrik Seipp

Planning is a fundamental task in artificial intelligence that involves finding a sequence of actions that achieve a specified goal in a given environment. Large language models (LLMs) are increasingly used for applications that require…

Computation and Language · Computer Science 2024-05-24 Eran Hirsch , Guy Uziel , Ateret Anaby-Tavor

Large language models (LLMs) hold promise for generating plans for complex tasks, but their effectiveness is limited by sequential execution, lack of control flow models, and difficulties in skill retrieval. Addressing these issues is…

Computation and Language · Computer Science 2024-10-18 Andrei Cosmin Redis , Mohammadreza Fani Sani , Bahram Zarrin , Andrea Burattin

Recent advances in Generative Artificial Intelligence, particularly Large Language Models (LLMs), have stimulated growing interest in automating or assisting Business Process Modeling tasks using natural language. Several approaches have…

Software Engineering · Computer Science 2026-04-16 João Bettencourt , Sérgio Guerreiro

Large language models (LLMs) have demonstrated significant capabilities in natural language processing and reasoning, yet their effectiveness in autonomous planning has been under debate. While existing studies have utilized LLMs with…

Computation and Language · Computer Science 2025-01-24 Bilgehan Sel , Ruoxi Jia , Ming Jin

Despite their linguistic competence, Large Language Models (LLMs) often struggle to reason reliably and flexibly. To identify these shortcomings, we introduce the Non-Linear Reasoning (NLR) dataset, a collection of 55 unique, hand-designed…

Computation and Language · Computer Science 2025-12-02 Nasim Borazjanizadeh , Steven T. Piantadosi

Classical and natural language planning tasks remain a difficult domain for modern large language models (LLMs). In this work, we lay the foundations for improving planning capabilities of LLMs. First, we construct a comprehensive benchmark…

Computation and Language · Computer Science 2024-11-05 Bernd Bohnet , Azade Nova , Aaron T Parisi , Kevin Swersky , Katayoon Goshvadi , Hanjun Dai , Dale Schuurmans , Noah Fiedel , Hanie Sedghi

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…

Artificial Intelligence · Computer Science 2024-09-04 Haoming Li , Zhaoliang Chen , Jonathan Zhang , Fei Liu

Motivated by the substantial achievements observed in Large Language Models (LLMs) in the field of natural language processing, recent research has commenced investigations into the application of LLMs for complex, long-horizon sequential…

Robotics · Computer Science 2023-08-29 Zhehua Zhou , Jiayang Song , Kunpeng Yao , Zhan Shu , Lei Ma

Large Language Models (LLMs) have been the subject of active research, significantly advancing the field of Natural Language Processing (NLP). From BERT to BLOOM, LLMs have surpassed state-of-the-art results in various natural language…

The pursuit of human-level artificial intelligence (AI) has significantly advanced the development of autonomous agents and Large Language Models (LLMs). LLMs are now widely utilized as decision-making agents for their ability to interpret…

Recent availability of Large Language Models (LLMs) has led to the development of numerous LLM-based approaches aimed at providing natural language interfaces for various end-user tasks. These end-user tasks in turn can typically be…

Artificial Intelligence · Computer Science 2025-02-14 Sudhir Agarwal , Anu Sreepathy , David H. Alonso , Prarit Lamba

The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over rigidly defined symbolic models, but also serves as a…

Automated planning is concerned with developing efficient algorithms to generate plans or sequences of actions to achieve a specific goal in a given environment. Emerging Large Language Models (LLMs) can answer questions, write high-quality…