mlsanityData to 14 Oct 2026

From Struggle (06-2024) to Mastery (02-2025) LLMs Conquer Advanced Algorithm Exams and Pave the Way for Editorial Generation

arXiv 2506.04965 ↗First posted 5 Jun 2025cs.CL cs.AIcited by 0

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Abstract (arXiv)

This paper presents a comprehensive evaluation of the performance of state-of-the-art Large Language Models (LLMs) on challenging university-level algorithms exams. By testing multiple models on both a Romanian exam and its high-quality English translation, we analyze LLMs' problem-solving capabilities, consistency, and multilingual performance. Our empirical study reveals that the most recent models not only achieve scores comparable to top-performing students but also demonstrate robust reasoning skills on complex, multi-step algorithmic challenges, even though difficulties remain with graph-based tasks. Building on these findings, we explore the potential of LLMs to support educational environments through the generation of high-quality editorial content, offering instructors a powerful tool to enhance student feedback. The insights and best practices discussed herein pave the way for further integration of generative AI in advanced algorithm education.

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References · 10

  1. 2024Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preferencecited by 1,184
  2. 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 619
  3. 2023Prompt Injection attack against LLM-integrated Applicationscited by 605
  4. 2025Competitive Programming with Large Reasoning Modelscited by 119
  5. 2023Applying Large Language Models and Chain-of-Thought for Automatic Scoringcited by 69
  6. 2024Unleashing Large Language Models' Proficiency in Zero-shot Essay Scoringcited by 33
  7. 2024Grade Like a Human: Rethinking Automated Assessment with Large Language Modelscited by 16
  8. 2024Examining the Behavior of LLM Architectures Within the Framework of Standardized National Exams in Brazilcited by 2
  9. 2025Exploring Large Language Models for Translating Romanian Computational Problems into Englishcited by 2
  10. 2025Automatic Feedback Generation for Short Answer Questions using Answer Diagnostic Graphscited by 1

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  3. 2025LLM-ProS: Analyzing Large Language Models' Performance in Competitive Problem Solving
  4. 2024Exploring the Capabilities of Prompted Large Language Models in Educational and Assessment Applications
  5. 2024Large Language Models for Education: A Survey
  6. 2025A Survey on Large Language Models with some Insights on their Capabilities and Limitations
  7. 2024The Future of Learning in the Age of Generative AI: Automated Question Generation and Assessment with Large Language Models
  8. 2025Simulating Student-Tutor Interactions with LLMs for Multilingual Math Feedback