Fabrizio Frasca
@ffabffrasca
Postdoctoral Fellow @TechnionLive — Geometric Deep Learning in some of its various forms — PhD @imperialcollege — Previously @twitter, @fabula_ai and @polimi
“Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality” is at #ICML2025! Drop by our poster on Tuesday 11:00–13:30, East Exhib. Hall A-B # E-3005. Joint work w/ @JoshSouthern13 @ytn_ym @GuyBarSh @mmbronstein @HaggaiMaron arxiv.org/abs/2501.03113 🧵
Heading to #ICML2025 in Vancouver 🇨🇦 July 13–19! 🚀Ping me if you want to discuss research and collabs on how to build better LLMs via: • Model merging & routing • Continual & modular learning • Distributed and Collaborative Learning
🌟 Tune in for GLOW's summer session this Wednesday! 🗓️ July 2nd, 5pm CEST on Zoom! 🌴@Rythian47 will present Tropical Attention for algo reasoning (arxiv.org/abs/2505.17190) 🧪 @jeremy_wayland will tell us about the intricacies of benchmarking GNNs (arxiv.org/abs/2502.02379)
Nice read! Also, have a look at our two ICML position papers: arxiv.org/abs/2502.14546 (Practice) and arxiv.org/abs/2402.02287 (Theory).
Check out this blogpost from @ffabffrasca and the GLOW reading group on the future of graph learning! I’ve also contributed and my main take is - its actually working and its an exciting moment to work on applications!
In the post, we write and elaborate on what emerged from one of our open discussion sessions. We touched upon where the community stands and where it may be headed next. Hope you enjoy the read 🤗 This is a joint effort by the GLOW organisers with inputs from many researchers!
Check out this blogpost from @ffabffrasca and the GLOW reading group on the future of graph learning! I’ve also contributed and my main take is - its actually working and its an exciting moment to work on applications!
Excited our paper got accepted and ICML 2025 — and looking forward to discussing this position with other researchers in July. ☺️ We are at a point where these kinds of interactions are extremely relevant in our community! Hope our contribution will foster them even more.
📣 Our spicy ICML 2025 position paper: “Graph Learning Will Lose Relevance Due To Poor Benchmarks”. Graph learning is less trendy in the ML world than it was in 2020-2022. We believe the problem is in poor benchmarks that hold the field back - and suggest ways to fix it! 🧵1/10
Come and see our new work at the “QUESTION” workshop today at #ICLR2025 ! We tackle Data Contamination and Hallucination Detection in LLMs with a learnable approach on their (structured) output signatures ☺️
📢 Introducing: Learning on LLM Output Signatures for Gray-box LLM Behavior Analysis [arxiv.org/pdf/2503.14043] A joint work with @ffabffrasca (co-first author) and our amazing collaborators: @dereklim_lzh @yoav_gelberg @YftahZ @el_yaniv @GalChechik @HaggaiMaron 🧵Thread
Apply if you are working on Geometric Deep Learning! LOGML is an amazing summer school. Attended twice as a student — got exposed to many new ideas and had the chance to connect with outstanding researchers. This year I will be joining as a mentor — hope to see you in London ☺️
🌟Applications open- LOGML 2025🌟 👥Mentor-led projects, expert talks, tutorials, socials, and a networking night ✍️Application form: logml.ai 📅Apply by 6th April 2025 ✉️Questions? [email protected] #MachineLearning #SummerSchool #LOGML #Geometry