{"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\/nb\/2024\/04\/claude-3-opus-blows-all-llms-away-in-book-length-summarization\/","title":{"rendered":"Claude 3 Opus sl\u00e5r alle LLM-er i boklange sammendrag"},"content":{"rendered":"

Forskere har publisert en studie som sammenligner n\u00f8yaktigheten og kvaliteten p\u00e5 sammendragene som LLM-er produserer. Claude 3 Opus gjorde det spesielt bra, men mennesker har fortsatt en fordel.<\/strong><\/p>\n

AI-modeller er ekstremt nyttige for \u00e5 oppsummere lange dokumenter n\u00e5r du ikke har tid eller lyst til \u00e5 lese dem.<\/p>\n

Luksusen med stadig st\u00f8rre kontekstvinduer betyr at vi kan sp\u00f8rre modellene med lengre dokumenter, noe som utfordrer deres evne til alltid \u00e5 f\u00e5 med seg fakta i sammendraget.<\/p>\n

Forskerne fra University of Massachusetts Amherst, Adobe, Allen Institute for AI og Princeton University, publisert en studie<\/a> som hadde som m\u00e5l \u00e5 finne ut hvor gode AI-modeller er til \u00e5 oppsummere innhold av boklengde (>100 000 tokens).<\/p>\n

FABLER<\/h2>\n

De valgte ut 26 b\u00f8ker som ble utgitt i 2023 og 2024, og fikk ulike LLM-er til \u00e5 oppsummere tekstene. De nylige utgivelsesdatoene ble valgt for \u00e5 unng\u00e5 potensiell dataforurensning i modellenes opprinnelige treningsdata.<\/p>\n

N\u00e5r modellene hadde produsert sammendragene, brukte de GPT-4 til \u00e5 trekke ut dekontekstualiserte p\u00e5stander fra dem. Forskerne hyret deretter inn menneskelige kommentatorer som hadde lest b\u00f8kene, og ba dem om \u00e5 faktasjekke p\u00e5standene.<\/p>\n

\"\"
LLM oppsummerer boken, GPT-4 trekker ut p\u00e5standene, og menneskelige kommentatorer verifiserer p\u00e5standene. Kilde: arXiv<\/figcaption><\/figure>\n

De resulterende dataene ble samlet i et datasett kalt \"Faithfulness Annotations for Book-Length Summarization\" (FABLES). FABLES inneholder 3158 annoteringer av trofasthet p\u00e5 p\u00e5standsniv\u00e5 i 26 narrative tekster.<\/p>\n

Testresultatene viste at Claude 3 Opus var \"det mest trofaste boklange sammendraget med en betydelig margin\", med over 90% av p\u00e5standene verifisert som trofaste eller n\u00f8yaktige.<\/p>\n

GPT-4 kom p\u00e5 en god andreplass, med bare 78% av p\u00e5standene verifisert som troverdige av de menneskelige kommentatorene.<\/p>\n

\"\"
Prosentandel av p\u00e5stander hentet fra LLM-genererte sammendrag vurdert av mennesker som trofaste, utro, delvis st\u00f8tte eller kan ikke verifiseres. Kilde: arXiv<\/figcaption><\/figure>\n

Den vanskelige delen<\/h2>\n

Modellene som ble testet, s\u00e5 alle ut til \u00e5 slite med de samme tingene. De fleste faktaene som modellene tok feil, var knyttet til hendelser eller tilstander hos karakterer og relasjoner.<\/p>\n

I artikkelen bemerkes det at \"de fleste av disse p\u00e5standene bare kan avkreftes ved hjelp av resonnementer over bevisene, noe som understreker oppgavens kompleksitet og forskjellen fra eksisterende innstillinger for faktaverifisering\".<\/p>\n

LLM-ene utelot ogs\u00e5 ofte kritisk informasjon i sammendragene sine. De legger ogs\u00e5 for stor vekt p\u00e5 innhold mot slutten av b\u00f8kene, og g\u00e5r glipp av viktig innhold n\u00e6rmere begynnelsen.<\/p>\n

Vil kunstig intelligens erstatte menneskelige kommentatorer?<\/h2>\n

Menneskelige kommentatorer eller faktasjekkere er dyre. Forskerne brukte $5 200 p\u00e5 \u00e5 f\u00e5 de menneskelige kommentatorene til \u00e5 verifisere p\u00e5standene i AI-sammendragene.<\/p>\n

Kunne en AI-modell ha gjort jobben billigere? Enkelt innhenting av fakta<\/a> er noe Claude 3 er god til, men n\u00e5r det gjelder \u00e5 verifisere p\u00e5stander som krever en dypere forst\u00e5else av innholdet, er den mindre konsekvent.<\/p>\n

N\u00e5r de ble presentert med de ekstraherte p\u00e5standene og bedt om \u00e5 verifisere dem, var alle AI-modellene d\u00e5rligere enn de menneskelige kommentatorene. De var spesielt d\u00e5rlige til \u00e5 identifisere utro p\u00e5stander.<\/p>\n

Selv om Claude 3 Opus var den beste p\u00e5standskontroll\u00f8ren med en viss avstand, konkluderte forskerne med at den \"til syvende og sist presterer for d\u00e5rlig til \u00e5 v\u00e6re en p\u00e5litelig automatisk sk\u00e5rer\".<\/p>\n

N\u00e5r det gjelder \u00e5 forst\u00e5 nyansene, de komplekse menneskelige relasjonene, plottpunktene og karakterenes motivasjon i en lang fortelling, ser det ut til at menneskene fortsatt har et forsprang.<\/p>","protected":false},"excerpt":{"rendered":"

Forskere har publisert en studie som sammenligner n\u00f8yaktigheten og kvaliteten p\u00e5 sammendragene som LLM-er produserer. Claude 3 Opus gjorde det spesielt bra, men mennesker har fortsatt en fordel. AI-modeller er ekstremt nyttige for \u00e5 oppsummere lange dokumenter n\u00e5r du ikke har tid eller lyst til \u00e5 lese dem. Luksusen med voksende kontekstvinduer betyr at vi kan be modellene om \u00e5 lese lengre dokumenter, noe som utfordrer deres evne til alltid \u00e5 f\u00e5 med seg fakta i sammendraget. Forskerne fra University of Massachusetts Amherst, Adobe, Allen Institute for AI og Princeton University publiserte en studie som fors\u00f8kte \u00e5 finne ut hvordan<\/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\/nb\/2024\/04\/claude-3-opus-blows-all-llms-away-in-book-length-summarization\/\" \/>\n<meta property=\"og:locale\" content=\"nb_NO\" \/>\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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