{"id":11410,"date":"2024-04-08T10:48:47","date_gmt":"2024-04-08T10:48:47","guid":{"rendered":"https:\/\/dailyai.com\/?p=11410"},"modified":"2024-04-08T10:48:47","modified_gmt":"2024-04-08T10:48:47","slug":"claude-3-opus-blows-all-llms-away-in-book-length-summarization","status":"publish","type":"post","link":"https:\/\/dailyai.com\/fr\/2024\/04\/claude-3-opus-blows-all-llms-away-in-book-length-summarization\/","title":{"rendered":"L'Opus Claude 3 fait miroiter \u00e0 tous les LLM la possibilit\u00e9 de faire un r\u00e9sum\u00e9 de leur livre"},"content":{"rendered":"

Des chercheurs ont publi\u00e9 une \u00e9tude comparant la pr\u00e9cision et la qualit\u00e9 des r\u00e9sum\u00e9s produits par les LLM. Claude 3 Opus s'est montr\u00e9 particuli\u00e8rement performant, mais l'homme garde l'avantage.<\/strong><\/p>\n

Les mod\u00e8les d'IA sont extr\u00eamement utiles pour r\u00e9sumer de longs documents lorsque vous n'avez pas le temps ou l'envie de les lire.<\/p>\n

Le luxe d'avoir des fen\u00eatres contextuelles de plus en plus grandes signifie que nous pouvons demander aux mod\u00e8les de pr\u00e9senter des documents plus longs, ce qui remet en question leur capacit\u00e9 \u00e0 toujours pr\u00e9senter les faits de mani\u00e8re claire dans le r\u00e9sum\u00e9.<\/p>\n

Les chercheurs de l'universit\u00e9 du Massachusetts Amherst, d'Adobe, de l'Allen Institute for AI et de l'universit\u00e9 de Princeton, a publi\u00e9 une \u00e9tude<\/a> qui visait \u00e0 d\u00e9terminer la capacit\u00e9 des mod\u00e8les d'IA \u00e0 r\u00e9sumer le contenu d'un livre (>100k tokens).<\/p>\n

FABLES<\/h2>\n

Ils ont s\u00e9lectionn\u00e9 26 livres publi\u00e9s en 2023 et 2024 et ont demand\u00e9 \u00e0 plusieurs LLM de r\u00e9sumer les textes. Les dates de publication r\u00e9centes ont \u00e9t\u00e9 choisies pour \u00e9viter une contamination potentielle des donn\u00e9es dans les donn\u00e9es d'apprentissage originales des mod\u00e8les.<\/p>\n

Une fois que les mod\u00e8les ont produit les r\u00e9sum\u00e9s, ils ont utilis\u00e9 GPT-4 pour en extraire les affirmations d\u00e9contextualis\u00e9es. Les chercheurs ont ensuite engag\u00e9 des annotateurs humains qui avaient lu les livres et leur ont demand\u00e9 de v\u00e9rifier les faits.<\/p>\n

\"\"
Le LLM r\u00e9sume le livre, le GPT-4 extrait les affirmations et les annotateurs humains v\u00e9rifient les affirmations. Source : arXiv<\/figcaption><\/figure>\n

Les donn\u00e9es obtenues ont \u00e9t\u00e9 compil\u00e9es dans un ensemble de donn\u00e9es appel\u00e9 \"Faithfulness Annotations for Book-Length Summarization\" (FABLES). FABLES contient 3 158 annotations de fid\u00e9lit\u00e9 au niveau des revendications dans 26 textes narratifs.<\/p>\n

Les r\u00e9sultats du test ont montr\u00e9 que Claude 3 Opus \u00e9tait \"le r\u00e9sum\u00e9 le plus fid\u00e8le d'un livre, avec une marge significative\", avec plus de 90% de ses affirmations v\u00e9rifi\u00e9es comme \u00e9tant fid\u00e8les ou exactes.<\/p>\n

Le GPT-4 arrive loin derri\u00e8re avec seulement 78% de ses affirmations v\u00e9rifi\u00e9es comme fid\u00e8les par les annotateurs humains.<\/p>\n

\"\"
Pourcentage d'affirmations extraites de r\u00e9sum\u00e9s g\u00e9n\u00e9r\u00e9s par LLM et \u00e9valu\u00e9es par des humains comme fid\u00e8les, infid\u00e8les, partiellement soutenues ou non v\u00e9rifiables. Source : arXiv<\/figcaption><\/figure>\n

La partie la plus difficile<\/h2>\n

Les mod\u00e8les test\u00e9s semblaient tous \u00e9prouver les m\u00eames difficult\u00e9s. La majorit\u00e9 des faits sur lesquels les mod\u00e8les se sont tromp\u00e9s concernaient des \u00e9v\u00e9nements ou des \u00e9tats des personnages et des relations.<\/p>\n

L'article note que \"la plupart de ces affirmations ne peuvent \u00eatre invalid\u00e9es que par un raisonnement \u00e0 plusieurs bonds sur les preuves, ce qui met en \u00e9vidence la complexit\u00e9 de la t\u00e2che et sa diff\u00e9rence par rapport aux contextes existants de v\u00e9rification des faits\".<\/p>\n

En outre, les MFR ont souvent omis des informations essentielles dans leurs r\u00e9sum\u00e9s. Ils accordent \u00e9galement trop d'importance au contenu vers la fin des livres, n\u00e9gligeant le contenu important situ\u00e9 au d\u00e9but.<\/p>\n

L'IA remplacera-t-elle les annotateurs humains ?<\/h2>\n

Les annotateurs humains ou les v\u00e9rificateurs de faits sont co\u00fbteux. Les chercheurs ont d\u00e9pens\u00e9 $5 200 euros pour que les annotateurs humains v\u00e9rifient les affirmations contenues dans les r\u00e9sum\u00e9s de l'IA.<\/p>\n

Un mod\u00e8le d'IA aurait-il pu faire le travail pour moins cher ? Simple recherche de faits<\/a> est un domaine dans lequel Claude 3 excelle, mais ses performances en mati\u00e8re de v\u00e9rification d'all\u00e9gations n\u00e9cessitant une compr\u00e9hension plus approfondie du contenu sont moins r\u00e9guli\u00e8res.<\/p>\n

Lorsqu'on leur a pr\u00e9sent\u00e9 les all\u00e9gations extraites et qu'on leur a demand\u00e9 de les v\u00e9rifier, tous les mod\u00e8les d'IA ont \u00e9t\u00e9 moins performants que les annotateurs humains. Ils ont particuli\u00e8rement mal r\u00e9ussi \u00e0 identifier les all\u00e9gations infid\u00e8les.<\/p>\n

Bien que Claude 3 Opus soit de loin le meilleur v\u00e9rificateur de sinistres, les chercheurs ont conclu qu'il \"est en fin de compte trop peu performant pour \u00eatre un \u00e9valuateur automatique fiable\".<\/p>\n

Lorsqu'il s'agit de comprendre les nuances, les relations humaines complexes, les intrigues et les motivations des personnages d'un long r\u00e9cit, il semble que les humains aient encore l'avantage pour l'instant.<\/p>","protected":false},"excerpt":{"rendered":"

Des chercheurs ont publi\u00e9 une \u00e9tude comparant la pr\u00e9cision et la qualit\u00e9 des r\u00e9sum\u00e9s produits par les LLM. Claude 3 Opus s'est particuli\u00e8rement bien comport\u00e9, mais les humains ont toujours l'avantage. Les mod\u00e8les d'IA sont extr\u00eamement utiles pour r\u00e9sumer de longs documents lorsque vous n'avez pas le temps ou l'envie de les lire. Le luxe d'avoir des fen\u00eatres contextuelles de plus en plus grandes signifie que nous pouvons demander aux mod\u00e8les de traiter des documents plus longs, ce qui remet en question leur capacit\u00e9 \u00e0 toujours pr\u00e9senter les faits avec exactitude dans le r\u00e9sum\u00e9. Les chercheurs de l'universit\u00e9 du Massachusetts Amherst, d'Adobe, de l'Allen Institute for AI et de l'universit\u00e9 de Princeton ont publi\u00e9 une \u00e9tude qui visait \u00e0 d\u00e9terminer comment les mod\u00e8les d'intelligence artificielle pouvaient s'adapter \u00e0 des documents plus longs.<\/p>","protected":false},"author":6,"featured_media":11415,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[118],"class_list":["post-11410","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-llms"],"yoast_head":"\nClaude 3 Opus blows all LLMs away in book-length summarization | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/fr\/2024\/04\/claude-3-opus-blows-all-llms-away-in-book-length-summarization\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Claude 3 Opus blows all LLMs away in book-length summarization | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Researchers published a study comparing the accuracy and quality of summaries that LLMs produce. Claude 3 Opus performed particularly well but humans still have the edge. AI models are extremely useful for summarizing long documents when you don\u2019t have the time or inclination to read them. The luxury of growing context windows means we get to prompt models with longer documents, which challenges their ability to always get the facts straight in the summary. 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