Repo · Benchmarks & research
codeforces-tag-prediction
Research benchmark for multi-label tagging of Codeforces problems comparing TypeSafe Jev against zero-shot LLMs, fine-tuned encoders, dense…
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Multi-label tagging of Codeforces problems: TypeSafe Jev against zero-shot LLMs, fine-tuned encoders, dense embeddings and TF-IDF, under one leak-free protocol.
benchmarkcodeforcesllmmachine-learningmlflowmulti-label-classificationxcodeeval
How builders describe it
Research benchmark for multi-label tagging of Codeforces problems comparing TypeSafe Jev against zero-shot LLMs, fine-tuned encoders, dense embeddings, and TF-IDF under one leak-free protocol.
The decision Jev makes
Benchmark questions with known answers, to check accuracy and confidence.
Where it fits
Head-to-head tests, calibration studies and independent research into how well Jev decides, how fast, and at what cost. All 682 benchmarks & research projects →
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