Giovanni Trappolini (@GioTrappolini) header
Giovanni Trappolini (@GioTrappolini) profile picture

Research Fellow in AI @Sapienza_Engineering

Joined December 2016
Photo by Giovanni Trappolini (@GioTrappolini)Photo by Giovanni Trappolini (@GioTrappolini)Photo by Giovanni Trappolini (@GioTrappolini)Photo by Giovanni Trappolini (@GioTrappolini)Photo by Giovanni Trappolini (@GioTrappolini)Photo by Giovanni Trappolini (@GioTrappolini)
It was great working with you Peter!
👩‍🔬AutoBench goes scientific!🎉Started 6 months ago almost as a game, then turned into business, now it's got a fancy arXiv paper to prove it's not just fun and money. Introducing the first scientific paper that validates our Collective-LLM-as-a-Judge method!🤖📜 1/12
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LLMs aren't humans, so why evaluate RAG with human-centric metrics? Traditional IR metrics fail to predict RAG performance because: ❌They assume sequential reading ❌They ignore that some docs actively distract LLMs Meet UDCG: a new metric w/ 36% ⬆️ corr. to actual performance✅
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Huge thanks to my amazing co-authors for making this work possible! 🙏 @FlorinCuconasu @SimoneFilice @Yoellem @fabreetseo (n/n)
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🚀Huge congratulations to Florin! 🏆 If reading the research paper isn't your thing, no worries—you can listen to the generated podcast instead, and it's actually pretty good. Quoting from it, "It's going to sound crazy! shorturl.at/NlVGc
Well done to our 'Best Poster Award' winners! One of our winners is @FlorinCuconasu with "The Power of Noise: Redefining Retrieval for RAG Systems". Congrats!! #M2LSummerSchool
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👀👀👀
Research published by Google Deepmind reveals OpenAI Strawberry's approach. Searches at inference through potential responses to reason better. “test-time compute can be used to outperform a 14× larger model.”
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Giovanni Trappolini retweeted
#ECIR2025 call for Tutorials: ecir2025.eu/call-for-tutoria…. Tutorial proposals submission: Nov. 08, 2024. Notification: Dec. 16, 2024.
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Almost ready for the second keynote here at the IR-RAG workshop! Finish up your lunch and come to the presidential ballroom for Dr. Zhang presentation! @yuhaozhangx
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"Seldom is a glance at the statistics enough to understand the meaning of the figures" 🤔 Fromm had clearly RAG in mind when uttering these words! ✍️ Read our paper to find out more about BaseVsInstruct for RAG! 🚩
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🚨 If you, or someone you know, are looking for a PhD you should definitely check this out! 🤌
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📢 Check out the refined version of “The Power of Noise: Redefining Retrieval for RAG Systems”! accepted @SIGIR2024. A huge thank you to the reviewers and the research community for your invaluable feedback—it has significantly improved the paper. (1/n)
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p.s. We have now added a statement clarifying that we use the instruct-version of the LLMs.
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