๐Ÿ“ฐ ใ‚ปใ‚ญใƒฅใƒชใƒ†ใ‚ฃใฃใฆ้›ฃใ—ใ„ (๐Ÿ‘ 44)

๐Ÿ‡ฌ๐Ÿ‡ง Explores structural challenges in enterprise security workโ€”beyond knowledge catchup, it's about deep system understanding.
๐Ÿ‡ฐ๐Ÿ‡ท ๊ธฐ์—… ๋ณด์•ˆ ์—…๋ฌด์˜ ๊ตฌ์กฐ์  ๋‚œ์ œโ€”์ง€์‹ ์Šต๋“์„ ๋„˜์–ด ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ๊นŠ์€ ์ดํ•ด๊ฐ€ ํ•„์š”.

๐Ÿ”— zenn.dev/mizutani/articles/sec

๐Ÿ“ฐ ไพ‹ใ‚’ๅข—ใ‚„ใ—ใŸใ‚‰LLMใฎๆ€ง่ƒฝใŒไธ‹ใŒใ‚‹ โ”€โ”€ few-shot collapseใฎ็™บ่ฆ‹ใจๆคœๅ‡บๆ–นๆณ• (๐Ÿ‘ 21)

๐Ÿ‡ฌ๐Ÿ‡ง Discovers few-shot collapse: more prompt examples can hurt LLM performance. AdaptGauge tool measures this on real tasks.
๐Ÿ‡ฐ๐Ÿ‡ท Few-shot collapse ๋ฐœ๊ฒฌ: ์˜ˆ์‹œ๋ฅผ ๋Š˜๋ฆฌ๋ฉด LLM ์„ฑ๋Šฅ์ด ์˜คํžˆ๋ ค ์ €ํ•˜. AdaptGauge๋กœ ์‹ค์ œ ์ž‘์—…์—์„œ ์ธก์ •.

๐Ÿ”— zenn.dev/okuma/articles/few_sh

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