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This research investigates the application of Large Language Models (LLMs) to augment conversational agents in process mining, aiming to tackle its inherent complexity and diverse skill requirements. While LLM advancements present novel…

Artificial Intelligence · Computer Science 2023-07-20 Urszula Jessen , Michal Sroka , Dirk Fahland

There is an growing interest in using Large Language Models (LLMs) in multi-agent systems to tackle interactive real-world tasks that require effective collaboration and assessing complex situations. Yet, we still have a limited…

Computation and Language · Computer Science 2024-06-11 Sahar Abdelnabi , Amr Gomaa , Sarath Sivaprasad , Lea Schönherr , Mario Fritz

Large Language Models (LLMs) have emerged as powerful tools for automating complex reasoning and decision-making tasks. In telecommunications, they hold the potential to transform network optimization, automate troubleshooting, enhance…

Multimodal Large Language Models (MLLMs) are gaining increasing popularity in both academia and industry due to their remarkable performance in various applications such as visual question answering, visual perception, understanding, and…

Computation and Language · Computer Science 2024-09-09 Jian Li , Weiheng Lu , Hao Fei , Meng Luo , Ming Dai , Min Xia , Yizhang Jin , Zhenye Gan , Ding Qi , Chaoyou Fu , Ying Tai , Wankou Yang , Yabiao Wang , Chengjie Wang

Large language models (LLMs) increasingly rely on external tools and APIs to execute complex tasks specified in natural language. Evaluating such tool calling capabilities in realistic enterprise settings is challenging: APIs are often…

Software Engineering · Computer Science 2026-01-27 Benjamin Elder , Anupama Murthi , Jungkoo Kang , Ankita Rajaram Naik , Kiran Kate , Kinjal Basu , Danish Contractor

Large Language Model (LLM) agents have shown great potential for solving real-world problems and promise to be a solution for tasks automation in industry. However, more benchmarks are needed to systematically evaluate automation agents…

Artificial Intelligence · Computer Science 2025-07-16 Yinsheng Li , Zhen Dong , Yi Shao

Competency modeling is widely used in human resource management to select, develop, and evaluate talent. However, traditional expert-driven approaches rely heavily on manual analysis of large volumes of interview transcripts, making them…

Computation and Language · Computer Science 2026-02-16 Silin Du , Manqing Xin , Raymond Jia Wang

The Graphical User Interface (GUI) is pivotal for human interaction with the digital world, enabling efficient device control and the completion of complex tasks. Recent progress in Large Language Models (LLMs) and Vision Language Models…

Artificial Intelligence · Computer Science 2024-06-14 Danyang Zhang , Zhennan Shen , Rui Xie , Situo Zhang , Tianbao Xie , Zihan Zhao , Siyuan Chen , Lu Chen , Hongshen Xu , Ruisheng Cao , Kai Yu

Large Language Models (LLMs) are transforming artificial intelligence, evolving into task-oriented systems capable of autonomous planning and execution. One of the primary applications of LLMs is conversational AI systems, which must…

Computation and Language · Computer Science 2025-01-22 Elad Levi , Ilan Kadar

Large Language Models (LLMs) are rapidly transforming various fields, and their potential in Business Process Management (BPM) is substantial. This paper assesses the capabilities of LLMs on business process modeling using a framework for…

Databases · Computer Science 2024-12-03 Humam Kourani , Alessandro Berti , Daniel Schuster , Wil M. P. van der Aalst

Workshop courses designed to foster creativity are gaining popularity. However, even experienced faculty teams find it challenging to realize a holistic evaluation that accommodates diverse perspectives. Adequate deliberation is essential…

Computers and Society · Computer Science 2025-07-04 Toru Ishida , Tongxi Liu , Hailong Wang , William K. Cheunga

Usability evaluation is an essential method to support the design of effective and intuitive user interfaces (UIs). However, it commonly relies on resource-intensive, expert-driven methods, which limit its accessibility, especially for…

Software Engineering · Computer Science 2026-04-13 Sebastian Lubos , Alexander Felfernig , Damian Garber , Gerhard Leitner , Julian Schwazer , Manuel Henrich

Large language models (LLMs) excel at answering questions but remain passive learners-absorbing static data without the ability to question and refine knowledge. This paper explores how LLMs can transition to interactive, question-driven…

Computation and Language · Computer Science 2025-06-03 Aum Kendapadi , Kerem Zaman , Rakesh R. Menon , Shashank Srivastava

Large Language Models (LLMs) are transforming scholarly tasks like search and summarization, but their reliability remains uncertain. Current evaluation metrics for testing LLM reliability are primarily automated approaches that prioritize…

Human-Computer Interaction · Computer Science 2026-02-25 Anna Martin-Boyle , William Humphreys , Martha Brown , Cara Leckey , Harmanpreet Kaur

There is much excitement about the opportunity to harness the power of large language models (LLMs) when building problem-solving assistants. However, the standard methodology of evaluating LLMs relies on static pairs of inputs and outputs,…

Large language models (LLMs) have been widely adopted across diverse domains of software engineering, such as code generation, program repair, and vulnerability detection. These applications require understanding beyond surface-level code…

Software Engineering · Computer Science 2026-01-21 Danning Xie , Mingwei Zheng , Xuwei Liu , Jiannan Wang , Chengpeng Wang , Lin Tan , Xiangyu Zhang

Large language models (LLMs) are powerful tools capable of handling diverse tasks. Comparing and selecting appropriate LLMs for specific tasks requires systematic evaluation methods, as models exhibit varying capabilities across different…

Computation and Language · Computer Science 2025-06-04 Anna Sokol , Elizabeth Daly , Michael Hind , David Piorkowski , Xiangliang Zhang , Nuno Moniz , Nitesh Chawla

The rapid progress of Multi-Modal Large Language Models (MLLMs) has spurred the creation of numerous benchmarks. However, conventional full-coverage Question-Answering evaluations suffer from high redundancy and low efficiency. Inspired by…

Computation and Language · Computer Science 2025-09-19 Ye Shen , Junying Wang , Farong Wen , Yijin Guo , Qi Jia , Zicheng Zhang , Guangtao Zhai

With the rapid advancement of Large Language Models (LLMs) in code generation, human-AI interaction is evolving from static text responses to dynamic, interactive HTML-based applications, which we term MiniApps. These applications require…

Artificial Intelligence · Computer Science 2026-05-11 Zuhao Zhang , Chengyue Yu , Yuante Li , Chenyi Zhuang , Linjian Mo , Shuai Li

Large language models (LLMs) have exhibited remarkable capabilities across diverse open-domain tasks, yet their application in specialized domains such as civil engineering remains largely unexplored. This paper starts bridging this gap by…

Computation and Language · Computer Science 2025-07-08 Jiachen Liu , Ziheng Geng , Ran Cao , Lu Cheng , Paolo Bocchini , Minghui Cheng
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