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This paper develops an agentic framework that employs large language models (LLMs) for grounded persuasive language generation in automated copywriting, with real estate marketing as a focal application. Our method is designed to align the…

Artificial Intelligence · Computer Science 2026-05-05 Jibang Wu , Chenghao Yang , Yi Wu , Simon Mahns , Chaoqi Wang , Hao Zhu , Fei Fang , Haifeng Xu

Although significant progress has been made in many tasks within the field of Natural Language Processing (NLP), Controlled Text Generation (CTG) continues to face numerous challenges, particularly in achieving fine-grained conditional…

Computation and Language · Computer Science 2025-09-18 Xinxu Zhou , Jiaqi Bai , Zhenqi Sun , Fanxiang Zeng , Yue Liu

Recommender systems are the cornerstone of today's information dissemination, yet a disconnect between offline metrics and online performance greatly hinders their development. Addressing this challenge, we envision a recommendation…

Information Retrieval · Computer Science 2024-11-11 An Zhang , Yuxin Chen , Leheng Sheng , Xiang Wang , Tat-Seng Chua

The development of large language models (LLMs) capable of following instructions and engaging in conversational interactions sparked increased interest in their utilization across various support tools. We investigate the utility of modern…

Human-Computer Interaction · Computer Science 2024-01-31 Tuhin Chakrabarty , Vishakh Padmakumar , Faeze Brahman , Smaranda Muresan

In this paper, we present Drama Llama, an LLM-powered storylets framework that supports the authoring of responsive, open-ended interactive stories. DL combines the structural benefits of storylet-based systems with the generative…

Human-Computer Interaction · Computer Science 2025-01-17 Yuqian Sun , Phoebe J. Wang , John Joon Young Chung , Melissa Roemmele , Taewook Kim , Max Kreminski

This technical report presents the Drama Engine, a novel framework for agentic interaction with large language models designed for narrative purposes. The framework adapts multi-agent system principles to create dynamic, context-aware…

Artificial Intelligence · Computer Science 2024-08-22 Martin Pichlmair , Riddhi Raj , Charlene Putney

Language-modeling--based approaches to story plot generation attempt to construct a plot by sampling from a language model (LM) to predict the next character, word, or sentence to add to the story. LM techniques lack the ability to receive…

Computation and Language · Computer Science 2023-01-19 Pradyumna Tambwekar , Murtaza Dhuliawala , Lara J. Martin , Animesh Mehta , Brent Harrison , Mark O. Riedl

Large Language Models (LLMs) offer a promising basis for creating agents that can tackle complex tasks through iterative environmental interaction. Existing methods either require these agents to mimic expert-provided trajectories or rely…

Computation and Language · Computer Science 2024-12-02 Dihong Gong , Pu Lu , Zelong Wang , Meng Zhou , Xiuqiang He

Autonomous agents driven by Large Language Models (LLMs) offer enormous potential for automation. Early proof of this technology can be found in various demonstrations of agents solving complex tasks, interacting with external systems to…

Within Multi Agent Systems, communication by means of Agent Communication Languages (ACLs) has a key role to play in the co-operation, co-ordination and knowledge-sharing between agents. Despite this, complex reasoning about agent…

Multiagent Systems · Computer Science 2015-08-12 David Lillis , Rem W. Collier`

We propose Camera Artist, a multi-agent framework that models a real-world filmmaking workflow to generate narrative videos with explicit cinematic language. While recent multi-agent systems have made substantial progress in automating…

Artificial Intelligence · Computer Science 2026-04-13 Haobo Hu , Qi Mao , Yuanhang Li , Libiao Jin

Automated plot generation for games enhances the player's experience by providing rich and immersive narrative experience that adapts to the player's actions. Traditional approaches adopt a symbolic narrative planning method which limits…

Human-Computer Interaction · Computer Science 2024-11-05 Yi Wang , Qian Zhou , David Ledo

Large Language Models (LLMs) have emerged as integral tools for reasoning, planning, and decision-making, drawing upon their extensive world knowledge and proficiency in language-related tasks. LLMs thus hold tremendous potential for…

Artificial Intelligence · Computer Science 2024-05-24 Xudong Guo , Kaixuan Huang , Jiale Liu , Wenhui Fan , Natalia Vélez , Qingyun Wu , Huazheng Wang , Thomas L. Griffiths , Mengdi Wang

Large Language Models (LLMs) have increasingly demonstrated the ability to facilitate the development of multi-agent systems that allow the interpretation of thoughts and actions generated by each individual. Promising advancements have…

Multiagent Systems · Computer Science 2024-09-24 Asher Sprigler , Alexander Drobek , Keagan Weinstock , Wendpanga Tapsoba , Gavin Childress , Andy Dao , Lucas Gral

Large Language Models (LLMs) have significantly impacted various domains, especially through organized LLM-driven autonomous agents. A representative scenario is in software development, where agents can collaborate in a team like humans,…

Computation and Language · Computer Science 2025-06-09 Zhuoyun Du , Chen Qian , Wei Liu , Zihao Xie , YiFei Wang , Rennai Qiu , Yufan Dang , Weize Chen , Cheng Yang , Ye Tian , Xuantang Xiong , Lei Han

Large Language Models (LLMs) hold great potential for web-based interactive applications, including browser games, online education, and digital storytelling platforms. However, LLM-based conversational agents suffer from spatiotemporal…

Human-Computer Interaction · Computer Science 2026-01-21 Geonwoo Bang , DongMyung Kim , Hayoung Oh

Interactive conversational recommender systems have gained significant attention for their ability to capture user preferences through natural language interactions. However, existing approaches face substantial challenges in handling…

Artificial Intelligence · Computer Science 2025-10-03 Bo Ma , Hang Li , ZeHua Hu , XiaoFan Gui , LuYao Liu , Simon Lau

Historically, scientific discovery has been a lengthy and costly process, demanding substantial time and resources from initial conception to final results. To accelerate scientific discovery, reduce research costs, and improve research…

Human-Computer Interaction · Computer Science 2025-06-18 Samuel Schmidgall , Yusheng Su , Ze Wang , Ximeng Sun , Jialian Wu , Xiaodong Yu , Jiang Liu , Michael Moor , Zicheng Liu , Emad Barsoum

Recent advancements in generative Large Language Models(LLMs) have been remarkable, however, the quality of the text generated by these models often reveals persistent issues. Evaluating the quality of text generated by these models,…

Computation and Language · Computer Science 2024-04-16 Yu Li , Shenyu Zhang , Rui Wu , Xiutian Huang , Yongrui Chen , Wenhao Xu , Guilin Qi , Dehai Min

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…

Computation and Language · Computer Science 2025-05-22 Jacob Kleiman , Kevin Frank , Joseph Voyles , Sindy Campagna
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