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  • LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in . . .
    Drawing on knowledge from a group of medalists in international algorithmic contests, we revisit this claim, examining how LLMs differ from human experts and where limitations still remain We introduce LiveCodeBench Pro, a benchmark composed of problems from Codeforces, ICPC, and IOI that are continuously updated to reduce the likelihood of
  • How Do Olympiad Medalists Judge LLMs in Competitive . . .
    A new benchmark assembled by a team of International Olympiad medalists suggests the hype about large language models beating elite human coders is premature LiveCodeBench Pro, unveiled in a 584-problem study [PDF] drawn from Codeforces, ICPC and IOI contests, shows the best frontier model clears j
  • 2025년 6월 16일 - by Kim Seonghyeon - arXiv Daily
    Recent reports claim that large language models (LLMs) now outperform elite humans in competitive programming Drawing on knowledge from a group of medalists in international algorithmic contests, we revisit this claim, examining how LLMs differ from human experts and where limitations still remain
  • LiveCodeBench Pro: Benchmarking LLMs in Competitive Programming
    Explore LiveCodeBench Pro, a contamination-resistant benchmark leveraging expert evaluation and real-time data curation to assess LLM performance on competitive programming challenges
  • ICPC-Eval: Probing the Frontiers of LLM Reasoning with . . .
    To address the challenges of inaccessible private test cases and the over-reliance on Online Judges, ICPC-Eval introduces a robust test case generation method This process utilizes large language models (LLMs) to synthesize C++ input data “generators” for each problem
  • Can Language Models Solve Olympiad Programming? - OpenReview
    Olympiad programming is one of the hardest reasoning challenges for humans, yet it has been understudied as a domain to benchmark language models (LMs) In this paper, we introduce the USACO
  • LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in . . .
    Recent reports claim that large language models (LLMs) now outperform elite humans in competitive programming …we revisit this claim, examining how LLMs differ from human experts and where limitations still remain





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