Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
80 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
7 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, and Evaluation Strategies (2403.06749v3)

Published 11 Mar 2024 in cs.DB

Abstract: Using LLMs for Process Mining (PM) tasks is becoming increasingly essential, and initial approaches yield promising results. However, little attention has been given to developing strategies for evaluating and benchmarking the utility of incorporating LLMs into PM tasks. This paper reviews the current implementations of LLMs in PM and reflects on three different questions. 1) What is the minimal set of capabilities required for PM on LLMs? 2) Which benchmark strategies help choose optimal LLMs for PM? 3) How do we evaluate the output of LLMs on specific PM tasks? The answer to these questions is fundamental to the development of comprehensive process mining benchmarks on LLMs covering different tasks and implementation paradigms.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (5)
  1. Alessandro Berti (35 papers)
  2. Humam Kourani (9 papers)
  3. Hannes Hafke (1 paper)
  4. Chiao-Yun Li (3 papers)
  5. Daniel Schuster (18 papers)
Citations (6)
X Twitter Logo Streamline Icon: https://streamlinehq.com