Sign in

Maria Sofia Bucarelli

@mariasofiab.bsky.social
69 followers 70 following 3 posts

👩‍🎓Postdoc Sapienza, Rome — PhD at Sapienza, Rome Previously Intern at Amazon Search, Lux — Visiting at Cambridge

PostsRepliesMedia
Reposted by Maria Sofia Bucarelli
Donato Crisostomi ✈️ NeurIPS @crisostomi.bsky.social · 11/03/2025
Will present this at #CVPR ✈️ See you in Nashville 🇺🇸! Kudos to the team 👏 Antonio A. Gargiulo, @mariasofiab.bsky.social, @sscardapane.bsky.social, Fabrizio Silvestri, Emanuele Rodolà.
052
Maria Sofia Bucarelli @mariasofiab.bsky.social · 20/02/2025
🚀Call for Submissions – @ai4coolerplanet.bsky.social Excited to announce the AI for a Cooler Planet workshop @ IJCNN 2025 in Rome 📅Submission Deadline: March 20, 2025 Topics include: 🌱 Climate Predictability, Physics-Informed ML, Weather Forecasting & more! 🔗 sites.google.com/view/ai4cool...
110
Reposted by Maria Sofia Bucarelli
Bruno Neri @neribr.bsky.social · 15/01/2025
"Task Singular Vectors: Reducing Task Interference in Model Merging" by Antonio Andrea Gargiulo, @crisostomi.bsky.social , @mariasofiab.bsky.social , @sscardapane.bsky.social, Fabrizio Silvestri, Emanuele Rodolà Paper: arxiv.org/abs/2412.00081 Code: github.com/AntoAndGar/t... #machinelearning
042
Reposted by Maria Sofia Bucarelli
Donato Crisostomi ✈️ NeurIPS @crisostomi.bsky.social · 08/01/2025
Don’t miss out on these insights and more — check out the paper! 📄 Preprint → arxiv.org/abs/2412.00081 💻 Code → github.com/AntoAndGar/t... Joint work w/ Antonio A. Gargiulo, @mariasofiab.bsky.social, @sscardapane.bsky.social, Fabrizio Silvestri, Emanuele Rodolà. (6/6)
arxiv.org
Task Singular Vectors: Reducing Task Interference in Model Merging
Task Arithmetic has emerged as a simple yet effective method to merge models without additional training. However, by treating entire networks as flat parameter vectors, it overlooks key structural in...
022
Reposted by Maria Sofia Bucarelli
Donato Crisostomi ✈️ NeurIPS @crisostomi.bsky.social · 08/01/2025
📢Prepend “Singular” to “Task Vectors” and get +15% average accuracy for free! 1. Perform a low-rank approximation of layer-wise task vectors. 2. Minimize task interference by orthogonalizing inter-task singular vectors. 🧵(1/6)
143
Maria Sofia Bucarelli @mariasofiab.bsky.social · 23/12/2024
🚀Calling ML on Graphs Enthusiasts! I'm co-organizign a Competition on Learning with Noisy Graph Labels at IJCNN 2025. Submissions are now open sites.google.com/view/learnin... Submission Deadline: 10/02/2025 We can’t wait to see your creative approaches and groundbreaking ideas.✨
sites.google.com
Sign in - Google Accounts
010