ML Research Scientist @Spotify. Personalization & GenAI. Previously: @eurecat_news, @Huawei, @UnivHelsinkiCS
Barcellona, Spagna
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Just 2 days ago, we posted the preprint on arXiv. What better way to share the news than getting @_akhaliq to tweet about it?🚀🎉
Check it out!
Spotify presents Personalized Audiobook Recommendations at Spotify Through Graph Neural Networks
In the ever-evolving digital audio landscape, Spotify, well-known for its music and talk content, has recently introduced audiobooks to its vast user base. While promising, this
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Francesco Fabbri retweeted
Want to do cheaper, statistically valid LLM evals?
Enter BetterEvals. It optimizes for real API costs (cached input / input / output) and uses confidence sequences, so you can stop sampling anytime without breaking validity.
betterevals.org/
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Francesco Fabbri retweeted
The teams really pulled out all the stops this year. We hope you like it! ❤️
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Francesco Fabbri retweeted
Excited to share our paper “Semantic IDs for Joint Generative Search & Recommendation” @ RecSys'25
🧠 Jointly fine-tuning embeddings for both tasks → shared Semantic IDs that work for search and recs ⚖️
📦 No more task-specific trade-offs!
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Francesco Fabbri retweeted
Happy to share our #recsys25 paper: “Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge”.
🧠 90 days of listening → natural-language user profiles → LLM judges alignment
📊 Aligns with human eval.
With amazing Spotify co-authors.
📄 arxiv.org/abs/2508.08777
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Francesco Fabbri retweeted
What if we could use off-the-shelf Multimodal Large Language Model to enrich current video recommendation models?
This is what we asked ourselves in our recent #recsys2025 paper arxiv.org/pdf/2508.09789
🧵
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Francesco Fabbri retweeted
Semantic IDs for Joint Generative Search and Recommendation
@_Guz_ et al. at Spotify introduce a bi-encoder model fine-tuned on both search and recommendation tasks to obtain item embeddings, followed by construction of unified Semantic ID space.
📝arxiv.org/abs/2508.10478
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Francesco Fabbri retweeted
Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge
Spotify introduces a profile-aware LLM framework for evaluating personalized podcast recommendations using natural-language user profiles distilled from listening history.
📝arxiv.org/abs/2508.08777
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Francesco Fabbri retweeted
Can we effectively detect covert Information Operations (IOs) that attempt to manipulate socio-political debates on social media?
This is the focus of our work, "IOHunter: Graph Foundation Model to Uncover Online Information Operations", just presented at the @RealAAAI
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Francesco Fabbri retweeted
Internship opportunity at Spotify!
PhD students, come join our Tech Research Team in London.
When: June-August 2025
Last day to apply is *February 6th, 2025* at 5 PM GMT.
Apply here lifeatspotify.com/jobs/2025-…
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Francesco Fabbri retweeted
What a Christmas gift🎁In our latest @RealAAAI paper, we integrate our coordination detection model with the power of LLMs & GNNs to enhance the generalizability of information operation (IO) detection in data-scarce scenarios and unseen IOs. Kudos to @FractalZucky and our🌠team!
"IOHunter: Graph Foundation Model to Uncover Online Information Operations" goes to @RealAAAI '25!
This is the result of an incredible collaboration with @LucaLuceri @Fra_Fabbri and @emilio__ferrara
Read the entire thread for a brief explanation and the link to the preprint.
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🚀🚀🚀
"IOHunter: Graph Foundation Model to Uncover Online Information Operations" goes to @RealAAAI '25!
This is the result of an incredible collaboration with @LucaLuceri @Fra_Fabbri and @emilio__ferrara
Read the entire thread for a brief explanation and the link to the preprint.
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Francesco Fabbri retweeted
I am recruiting 1-2 PhD students for Fall 2025 at Princeton to work on Comp Social Science/Societal Impact of GenAI/GenAI for SocSci
I wrote a bit about my research flavor & interests here: manoelhortaribeiro.github.io…
Deadline: December 15th (cs.princeton.edu/grad#prospe…)
Please boost!
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Francesco Fabbri retweeted
📢 I’m recruiting PhD students for Fall'25 in @Berkeley_EECS or @UCJointCPH! Please apply if you have related interests in AI for social good / networks / public health / social science
See my website for more on my research and how to apply: serinachang5.github.io/
Please RT!
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Francesco Fabbri retweeted
It was a true honour to present our research at Spotify during #RecSys2024. Sharing our work in such a unique theatre setting was an unforgettable experience. Thank you to everyone involved!
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Francesco Fabbri retweeted
🎉Excited to share: "Algorithmic Drift: A Simulation Framework to Study the Effects of Recommender Systems on User Preferences". Joint work with
@EricaCoppolillo, @simone_mungari, @EttoreRitacco, @Fra_Fabbri, @FractalZucky, @FrancescoBonchi
arxiv.org/abs/2409.16478
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Francesco Fabbri retweeted
Uncovering Coordinated Cross-Platform Information Operations Threatening the Integrity of the 2024 U.S. Presidential Election Online Discussion
w/ @emilio__ferrara @FractalZucky @Federico_Cinus
View our findings here: papers.ssrn.com/sol3/papers.…
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Francesco Fabbri retweeted
🚨Hiring alert!
My team @SpotifyResearch is looking to hire a research scientist with a machine learning background! Come help us improve personalization experiences by integrating innovative generative AI technologies into our recommender systems. lifeatspotify.com/jobs/resea…
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Francesco Fabbri retweeted
Video data is widely available but has been difficult to analyze automatically
Particularly, TV data is a rich and important source of information for millions.
We have a paper at #KDD2024 making such data accessible.
Paper: gvrkiran.github.io/content/T…
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Super excited to welcome @kdd_news in Barcelona 🚀
I’ll be at the conference this week, so feel free to ping me to talk about GNNs, GenAI for recs or anything Barcelona related 🎉
Waiting for #kdd2024 what’s better than Barça 🔴🔵 game? Thanks @Fra_Fabbri @SpotifyResearch for the invite!
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