Adversarial competition between attacker and defender teams generates diverse multi-turn conversational data that improves LLM performance on secure code generation benchmarks by 18-29%.
2406.12397 , archivePrefix=
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PuckTrick library adds controlled imperfections to synthetic data and shows that models trained on the resulting contaminated data outperform those trained on clean synthetic data in financial dataset experiments.
citing papers explorer
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Adversarial Arena: Crowdsourcing Data Generation through Interactive Competition
Adversarial competition between attacker and defender teams generates diverse multi-turn conversational data that improves LLM performance on secure code generation benchmarks by 18-29%.
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PuckTrick: A Library for Making Synthetic Data More Realistic
PuckTrick library adds controlled imperfections to synthetic data and shows that models trained on the resulting contaminated data outperform those trained on clean synthetic data in financial dataset experiments.