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LLM-as-a-Judge ã¨ãƒ«ãƒ¼ãƒ–リック評価
ã“ã®è¨˜äº‹ã«ã¤ã„㦠本記事㯠Ubie Tech Advent Calendar 2025 19 日目ã®è¨˜äº‹ã§ã™ï¼ LLM を活用ã—ãŸãƒ—ãƒãƒ€ã‚¯ãƒˆé–‹ç™ºã«ãŠã„ã¦ã€ã€Œç”Ÿæˆçµæžœã®å“質をã©ã†è©•ä¾¡ã™ã‚‹ã‹ã€ã¯å¸¸ã«å¤§ããªèª²é¡Œã§ã™ã€‚ モデルã®æ›´æ–°ã€ãƒ—ãƒãƒ³ãƒ—トã®æ”¹å–„ã€RAG ã®æ¤œç´¢ç²¾åº¦ã®å‘上ãªã©ã€ã‚らゆる改善活動ã«ãŠã„ã¦ã€ä¿¡é ¼ã§ãる「評価指標（メトリクス）ã€ãŒãªã‘ã‚Œã°ã€ãã‚ŒãŒæ”¹å–„ãªã®ã‹æ”¹æ‚ªãªã®ã‹ã‚’判æ–ã§ãã¾ã›ã‚“。 Ubie ã§ã¯ã€LLM を活用ã—ãŸç”Ÿæ´»è€…ã®å¥åº·ã«é–¢ã™ã‚‹ç›¸è«‡ã«å¿œç”ã™ã‚‹ã‚¢ãƒ—リケーションã®é–‹ç™ºãƒ»é‹ç”¨ã—ã¦ã„ã¾ã™ã€‚医療・å¥åº·ã¨ã„ã†ãƒ‰ãƒ¡ã‚¤ãƒ³ã®ç‰¹æ€§ä¸Šã€æ£ç¢ºæ€§ã‚„安全性ã«ã¯é«˜ã„水準ãŒæ±‚ã‚られã¾ã™ã€‚ã¾ãŸã€"Helpfulness"（有用性）や "Empathy"（共感性）ã¨ã„ã£ãŸå®šæ€§çš„ãªä¾¡å€¤ã‚‚åŒæ™‚ã«æ‹…ä¿ã™ã‚‹å¿…è¦ãŒã‚ã‚Šã¾ã™ã€‚ ã“ã®ã‚ˆã†ãªè¤‡é›‘ãªè¦ä»¶ã‚’満ãŸã™ãŸã‚ã€ç§ãŸã¡ã¯ LLM-as-a-Judge （LLM ã«ã‚ˆã‚‹è‡ª
実践Claude Code入門 | 技術評論社
著者 西見公å®ï¼ˆã«ã—ã¿ã¾ã•ã²ã‚），å‰ç”°çœŸå¾ï¼ˆã‚ˆã—ã ã—ã‚“ã”），大嶋勇樹（ãŠãŠã—ã¾ã‚†ã†ã）　著 定価 3,300円（本体3,000円＋税10%） 発売日 2025.12.26 判型 B5変形 é æ•° 304ページ ISBN 978-4-297-15354-0 978-4-297-15355-7 æ¦‚è¦ æœ¬æ›¸ã¯ã€Claude Codeã®åŸºæœ¬çš„ãªä½¿ã„æ–¹ã‹ã‚‰ã¯ã˜ã‚ã€ã‚¹ãƒšãƒƒã‚¯é§†å‹•é–‹ç™ºã‚’マスターã™ã‚‹ã“ã¨ã§ã€å¤§è¦æ¨¡è¨€èªžãƒ¢ãƒ‡ãƒ«ï¼ˆLLM）ã¨ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ãƒªãƒ³ã‚°ã‚’çµ±åˆã™ã‚‹æ–¹æ³•ã‚’解説ã—ãŸæ›¸ç±ã§ã™ã€‚Claude Codeã‚’ã¯ã˜ã‚ã¨ã—ãŸã•ã¾ã–ã¾ãªã‚³ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°ã‚¨ãƒ¼ã‚¸ã‚§ãƒ³ãƒˆã¯ã€å˜ãªã‚‹ã€Œé”法ã®ã‚ˆã†ã«ã‚³ãƒ¼ãƒ‰ã‚’生æˆã™ã‚‹AI機能ã€ã§ã¯ã‚ã‚Šã¾ã›ã‚“。LLMã®è‡ªå¾‹çš„ãªæŽ¨è«–能力ã¨ã‚¨ãƒ¼ã‚¸ã‚§ãƒ³ãƒˆãƒ•ãƒ¬ãƒ¼ãƒ ワークã®æ©Ÿèƒ½æ€§ã‚’çµ±åˆã™ã‚‹ã“ã¨ã§ã€è¦æ±‚ã®ç²¾ç·»åŒ– → é”æˆã™ã‚‹ãŸã‚ã®è¨ˆç”»ç«‹æ¡ˆ → タスクã®å®Ÿè¡Œ → 実行çµæžœã®æ¤œè¨¼ã¨ã„ã†ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢é–‹ç™ºã«ãŠ
Useful patterns for building HTML tools
10th December 2025 I’ve started using the term HTML tools to refer to HTML applications that I’ve been building which combine HTML, JavaScript, and CSS in a single file and use them to provide useful functionality. I have built over 150 of these in the past two years, almost all of them written by LLMs. This article presents a collection of useful patterns I’ve discovered along the way. First, som
LMArena | Benchmark & Compare the Best AI Models
Find the best AI for youCompare answers across top AI models, share your feedback and power our public leaderboard Your conversations and certain other personal information will be disclosed to the relevant AI providers and may otherwise be disclosed publicly to help support our community and advance AI research. Do not submit to our Services any personal information or other sensitive information
Mixboard
Mixboard is an AI-powered concepting board that helps you explore, expand, and refine your ideas.
Storybook Design Systems with Agents RFC · storybookjs/ds-mcp-experiment-reshaped · Discussion #1
Storybook generates a manifest file for all components. It is a JSON file containing all the available metadata about components (name, props, examples, etc.) as well as any documentation (MDX) pages. As this could get big very fast, each component is separated into its own JSON file, referenced by the main components-manifest.json. Storybook’s Dev server will dynamically serve these manifests at
カスタマーサクセスã‹ã‚‰ã®èª¿æŸ»ä¾é ¼ã‚’効率化ï¼Ask Devin×GAS×Slackã«ã‚ˆã‚‹è‡ªå‹•èª¿æŸ»ã®æ§‹ç¯‰ - TalentX Tech Blog
ã“ã‚“ã«ã¡ã¯ã€‚MyTalent開発ã®ç©´åŽŸã§ã™ã€‚ SaaSã‚’é‹ç”¨ã—ã¦ã„ã‚‹ä¸ã§CS(カスタマーサクセス)ã‹ã‚‰èª¿æŸ»ä¾é ¼ã‚’å—ã‘ã‚‹ã“ã¨ãŒã‚ã‚Šã¾ã™ã€‚ 本記事ã§ã¯èª¿æŸ»å·¥æ•°ã‚’減らã™ãŸã‚ã«Ask Devinを活用ã—ãŸå–り組ã¿ã‚’紹介ã—ã¾ã™ã€‚ Ask Devinã¨ã¯ TalentXã®èª¿æŸ»ä¾é ¼ãƒ•ãƒãƒ¼ 処ç†ã®ãƒ•ãƒãƒ¼ 一連ã®å‡¦ç†ã‚’ä½œæˆ Slack ワークフãƒãƒ¼ã®ä½œæˆã€Google ã‚¹ãƒ—ãƒ¬ãƒƒãƒ‰ã‚·ãƒ¼ãƒˆé€£æº GASã®ä½œæˆ Ask Devinã«è³ªå•å†…容をリクエストã™ã‚‹ 実装 Ask Devinã¸ã®ãƒªã‚¯ã‚¨ã‚¹ãƒˆãŒå¤±æ•—ã™ã‚‹å ´åˆ Google スプレッドシートã¸ã®è¨˜éŒ²ã‚’トリガーã«èµ·å‹•ã•ã›ã‚‹ 実際ã«èª¿æŸ»ã‚’ãŠé¡˜ã„ã—ã¦ã¿ãŸã€‚ ã¾ã¨ã‚ 最後㫠Ask Devinã¨ã¯ Ask Devinã¯DevinãŒæä¾›ã™ã‚‹æ©Ÿèƒ½ã®ä¸€ã¤ã§ã™ã€‚ devin.ai Devinã¨ã¯é•ã„ã€ãƒ—ãƒã‚°ãƒ©ãƒ を作æˆã—ãŸã‚Šgithub上ã®ãƒ—ルリクエストをレビューã—ã¦ã‚‚らã†ã“ã¨ã¯ã§ã
Copilot code review: Path-scoped custom instruction file support - GitHub Changelog
Menu. Currently selected: Path-scoped instruction files now supported in Copilot code review Copilot code review is becoming even more customizable! You can now use your existing path-scoped instruction files to provide targeted guidance for specific parts of your repository. Plus we have a few other important updates for you to know about. 👇 Path-scoped instruction files now supported in Copilot
Designing the Built-in AI Web APIs
For the last year, I’ve been working as part of the Chrome built-in AI team on a set of APIs to bring various AI models to the web browser. As with all APIs we ship, our goal is to make these APIs compelling enough that other browsers adopt them, and they become part of the web’s standard library. Working in such a fast-moving space brings tension with the usual process for building web APIs. When
Perplexity is using stealth, undeclared crawlers to evade website no-crawl directives
Perplexity is using stealth, undeclared crawlers to evade website no-crawl directives2025-08-04 We are observing stealth crawling behavior from Perplexity, an AI-powered answer engine. Although Perplexity initially crawls from their declared user agent, when they are presented with a network block, they appear to obscure their crawling identity in an attempt to circumvent the website’s preferences
Defeating Prompt Injections by Design
Large Language Models (LLMs) are increasingly deployed in agentic systems that interact with an untrusted environment. However, LLM agents are vulnerable to prompt injection attacks when handling untrusted data. In this paper we propose CaMeL, a robust defense that creates a protective system layer around the LLM, securing it even when underlying models are susceptible to attacks. To operate, CaMe
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Agent Deck - Your AI Agent Command Center
GitHub - PleasePrompto/notebooklm-skill: Use this skill to enable Claude Code to communicate directly with your Google NotebookLM notebooks. Query your uploaded documents and get source-grounded, citation-backed answers from Gemini. Features browser autom
Why We Fear AI — Common Notions Press
CASCADE: LLM-Powered JavaScript Deobfuscator at Google
GitHub - sumik5/llm-translate
AI coding assistants wave goodbye to junior developers
Try-on API - Virtual Try-On API for Developers
GitHub - microsoft/poml: Prompt Orchestration Markup Language
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