Toward LLM self-play under data scarcity: effectiveness, generalizability, and trustworthiness
Read the original at arxiv.org→arXiv:2611.08908v1 Announce Type: new Abstract: The rapid development of large language models (LLMs) has been driven largely by scaling model size and human-curated training data, yet this paradigm is increasingly...
Original headline: "Toward LLM Self-Play Under Data Scarcity: Effectiveness, Generalizability, and Trustworthiness"
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- Nov 9, 05:00 UTC arXiv cs.AI lead source Toward LLM Self-Play Under Data Scarcity: Effectiveness, Generalizability, and Trustworthiness