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标题为英语Benchmarking Prompt Optimization of Large Language Models With Chess

Evaluating large language models becomes increasingly challenging as their capabilities advance: benchmarks can saturate, public test sets risk contamination, and assessing harder tasks can require expensive grading or execution infrastructure. These challenges are amplified in…

arXiv — cs.AI作者: Timoth\'ee Lesort, Alejandra L\'opez de Aberasturi G\'omez, Tristan Karch, Tom Veniat, Philippe Modard, Karl Tuyls, Ludovic Denoyer2026年10月2日 (10月2日)
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  • Evaluating large language models becomes increasingly challenging as their capabilities advance: benchmarks can saturate, public test sets risk contamination, and assessing harder tasks can require expensive grading or execution infrastructure
  • These challenges are amplified in…
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Benchmarking Prompt Optimization of Large Language Models With Chess

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