RSTLess group

147 posts

RSTLess group

RSTLess group

@RSTLessGroup

@SapienzaRoma, @DIAGSapienza Research Group PI: Fabrizio Silvestri @fabreetseo

Rome, Italy Bergabung Nisan 2024
193 Mengikuti151 Pengikut
RSTLess group
RSTLess group@RSTLessGroupยท
Alessia Borghini is a first-year PhD student in the National Doctorate in AI supervised by Fabrizio Silvestri. Her research focuses on Mechanistic Interpretability for #AISafety, aiming to understand LLMs and improve alignment and reliability. Fell free to reach out!!
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RSTLess group
RSTLess group@RSTLessGroupยท
Alessio Borgi is a PhD student in Graph Neural Networks & Generative AIโ€”bridging geometry, topology, and diffusion models for robotics, vision, and biomedical AI. Feel free to contact him for collaborations. #AI #GNN #GenerativeAI #Robotics #RSTLess #Sapienza
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RSTLess group
RSTLess group@RSTLessGroupยท
Gavriel Di Nepi is a first-year PhD student in Data Science at Sapienza under the supervision of prof. @fabreetseo . His research focuses on human-inspired memory for #AI to boost performance and reasoning, in collaboration with @bakerhughesco. #RSTLess #Sapienza
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RSTLess group
RSTLess group@RSTLessGroupยท
Meet Maria Vittoria Vestini, 1st-year PhD student in Data Science at Sapienza University of Rome, supervised by @fabreetseo. Her research explores interactions and learning dynamics between large and small language models. Learn more: rstless.it #RSTLess #Sapienza
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RSTLess group
RSTLess group@RSTLessGroupยท
By combining the expressive power of sheaves with a principled treatment of directionality, our method achieves consistent relative accuracy improvements over prior methods.
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RSTLess group
RSTLess group@RSTLessGroupยท
- We introduce the notion of Directed Cellular Sheaves over directed hypergraphs - From this construction, we derive the Directed Sheaf Hypergraph Laplacian, a complex-valued Hermitian operator that unifies and generalizes existing graph and hypergraph convolutional operators.
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RSTLess group
RSTLess group@RSTLessGroupยท
It presents theoretical and empirical results answering to the question: "๐ถ๐‘Ž๐‘› ๐‘€๐‘Ž๐‘—๐‘œ๐‘Ÿ๐‘–๐‘ก๐‘ฆ ๐‘‰๐‘œ๐‘ก๐‘–๐‘›๐‘” ๐‘Ž๐‘โ„Ž๐‘–๐‘’๐‘ฃ๐‘’ ๐‘กโ„Ž๐‘’ ๐‘กโ„Ž๐‘’๐‘œ๐‘Ÿ๐‘’๐‘ก๐‘–๐‘๐‘Ž๐‘™๐‘™๐‘ฆ ๐‘œ๐‘๐‘ก๐‘–๐‘š๐‘Ž๐‘™ ๐‘™๐‘Ž๐‘๐‘’๐‘™ ๐‘’๐‘ ๐‘ก๐‘–๐‘š๐‘Ž๐‘ก๐‘–๐‘œ๐‘› ๐‘’๐‘Ÿ๐‘Ÿ๐‘œ๐‘Ÿ ๐‘Ž๐‘›๐‘‘ ๐‘ข๐‘›๐‘‘๐‘’๐‘Ÿ ๐‘คโ„Ž๐‘Ž๐‘ก ๐‘๐‘œ๐‘›๐‘‘๐‘–๐‘ก๐‘–๐‘œ๐‘›๐‘ ?"
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RSTLess group
RSTLess group@RSTLessGroupยท
๐“๐ก๐ž ๐Œ๐š๐ฃ๐จ๐ซ๐ข๐ญ๐ฒ ๐•๐จ๐ญ๐ข๐ง๐  ๐๐š๐ซ๐š๐๐ข๐ ๐ฆ ๐’๐ก๐ข๐Ÿ๐ญ: ๐–๐ก๐ž๐ง ๐๐จ๐ฉ๐ฎ๐ฅ๐š๐ซ ๐Œ๐ž๐ž๐ญ๐ฌ ๐Ž๐ฉ๐ญ๐ข๐ฆ๐š๐ฅ accepted at #AISTATS2026! Work done by @AntonioPuri00, @mariasofiabuc, Anil Kumar Nelakanti, @Andrea_Bacciu, @amantrac, @fabreetseo! Paper arxiv.org/pdf/2502.12581
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RSTLess group
RSTLess group@RSTLessGroupยท
5/5 This offers a complementary perspective on mechanistic interpretability: from finding circuits to shaping and composing them during learning. Looking forward to discussions at #ICLR! Thanks to Samuele Fonio, Simone Monaco Nicola Saccomanno and @fabreetseo !
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RSTLess group
RSTLess group@RSTLessGroupยท
4/5 Crucially, these circuits are composable. We show they can be recombined into generalist models, behaving like modular building blocks rather than isolated explanations.
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RSTLess group
RSTLess group@RSTLessGroupยท
3/5 We introduce a training-time objective that steers circuit formation toward specific concepts. After training, we use pruning to extract class-specific circuits: functional subnetworks specialized for a subset of classes.
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RSTLess group
RSTLess group@RSTLessGroupยท
2/5 Most mechanistic interpretability work finds circuits post hoc, after training a model. We ask a different question: can we control which concepts shape circuits during training?
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RSTLess group
RSTLess group@RSTLessGroupยท
Paper accepted at #AISTATS2026!! ๐‘๐š๐ง๐ค ๐‹๐ข๐Ÿ๐ญ๐ข๐ง๐  ๐š๐ง๐ ๐‘๐š๐ง๐๐จ๐ฆ ๐๐จ๐ง-๐‹๐ข๐ง๐ž๐š๐ซ ๐Œ๐š๐ฉ๐ฌ: once the size of a one-hidden-layer neural network exceeds a threshold, the hidden representations are linearly independent with high probability. #RSTLess #Sapienza
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RSTLess group
RSTLess group@RSTLessGroupยท
@chiaradercoli is 1st-year PhD student in the National Doctorate in AI, supervised by @pl219_Cambridge . ๐Ÿ”ฌ AI for Medicine | Digital Twins | ODEs ๐Ÿงฌ RNA pathways (T1D, Periodontitis) ๐Ÿค– LLMs for clinical & biomedical data Open to collaborations! feel free to reach out
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RSTLess group@RSTLessGroupยท
Meet @Ali_Ghasemi7899 ๐Ÿš€ New PhD of our group under the supervision of @fabreetseo working on Efficient LLMs & LLM Agents exploring methods to optimize LLMs. He holds a MSc in Artificial Intelligence and Robotics (graduated with full marks and honors). #RSTLess #Sapienza #AI #LLM
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