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Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, and Evaluation Strategies
5 references·2 citing·26 second hop
Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, and Evaluation Strategies (2024)Evaluating Large Language Models in Proce…Large Process Models: A Vision for Business Process Management in the Age of Generative AI (2024)Large Process Models: A Visio…Large Language Models Can Accomplish Business Process Management Tasks (2024)Large Language Models Can Acc…Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena (2023)Judging LLM-as-a-Judge with M…DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models (2023)DecodingTrust: A Comprehensiv…Process Mining (2016)Process MiningOn the potential of large language models to solve semantics-aware process mining tasks (2025)On the potential of large lan…Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining Tasks (2024)Evaluating the Ability of LLM…Process Model Generation from Natural Language Text (2011)Conformance checking based on multi-perspective declarative process models (2016)Large Language Models for Business Process Management: Opportunities and Challenges (2023)Conversing with business process-aware large language models: the BPLLM framework (2024)Evaluating large language models on business process modeling: framework, benchmark, and self-improvement analysis (2025)PM-LLM-Benchmark: Evaluating Large Language Models on Process Mining Tasks (2025)On Bullshit (2005)Digital Nudging (2016)Fundamentals of Business Process Management (2018)Conversational Systems for AI-Augmented Business Process Management (2024)Mapping the Landscape: Exploring Large Language Model Applications in Business Process Management (2024)Resource allocation in business process executions—A systematic literature study (2025)Process Mining and Security: Detecting Anomalous Process Executions and Checking Process Conformance (2005)Predicting process behaviour using deep learning (2017)A systematic literature review on state-of-the-art deep learning methods for process prediction (2021)Discovering Block-Structured Process Models from Event Logs - A Constructive Approach (2013)Conformance Checking (2018)Automated Discovery of Process Models from Event Logs: Review and Benchmark (2018)Outcome-Oriented Predictive Process Monitoring (2019)Examining the interplay between big data analytics and contextual factors in driving process innovation capabilities (2020)A Reasoning and Value Alignment Test to Assess Advanced GPT Reasoning (2024)Risks from Language Models for Automated Mental Healthcare: Ethics and Structure for Implementation (2024)Survey on AI-Generated Plagiarism Detection: The Impact of Large Language Models on Academic Integrity (2024)Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models (2024)Assessing and Understanding Creativity in Large Language Models (2025)Hallucination‐Free? Assessing the Reliability of Leading AI Legal Research Tools (2025)
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References

  • 2016Process Mining2,166 cited
  • 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena1,838 cited
  • 2024Large Language Models Can Accomplish Business Process Management Tasks118 cited
  • 2023DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models105 cited
  • 2024Large Process Models: A Vision for Business Process Management in the Age of Generative AI66 cited

Cited by

  • 2025On the potential of large language models to solve semantics-aware process mining tasks19 cited
  • 2024Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining Tasks19 cited

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