Evals & Safety
A coding benchmark that keeps collecting new problems from LeetCode, AtCoder, and Codeforces contests over time, so models can be scored only on problems published after their training cutoff.
A coding benchmark that keeps collecting new problems from LeetCode, AtCoder, and Codeforces contests over time, so models can be scored only on problems published after their training cutoff. That release-date filtering is how it limits data contamination, a known weakness of fixed sets like HumanEval. Beyond code generation, it also tests self-repair, code execution, and test output prediction.
Primary source: arxiv.org
Example
That release-date filtering is how it limits data contamination, a known weakness of fixed sets like HumanEval.
Hands-on guides, comparisons, and tutorials that cover Evals & Safety.
FAQ
A coding benchmark that keeps collecting new problems from LeetCode, AtCoder, and Codeforces contests over time, so models can be scored only on problems published after their training cutoff.
LiveCodeBench sits in the Evals & Safety part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Developers Digest publishes tutorials and videos that cover Evals & Safety topics including LiveCodeBench. Check the blog and YouTube channel for hands-on walkthroughs.
Related
A general LLM benchmark built to resist test set contamination by adding new questions every month from recent sources such as math competitions, arXiv papers, news articles, and datasets.
Benchmark contamination happens when a model's training data contains the questions or answers from an evaluation benchmark.
A code editing benchmark from the Aider project built from the 225 hardest Exercism exercises across C++, Go, Java, JavaScript, Python, and Rust.

New tutorials, open-source projects, and deep dives on coding agents - delivered weekly.