Biggio, Luca

13 publications

ICML 2025 Counting in Small Transformers: The Delicate Interplay Between Attention and Feed-Forward Layers Freya Behrens, Luca Biggio, Lenka Zdeborova

NeurIPS 2025 On the Bias of Next-Token Predictors Toward Systematically Inefficient Reasoning: A Shortest-Path Case Study Riccardo Alberghi, Elizaveta Demyanenko, Luca Biggio, Luca Saglietti

ICMLW 2024 Understanding Counting in Small Transformers: The Interplay Between Attention and Feed-Forward Layers Freya Behrens, Luca Biggio, Lenka Zdeborova

ICML 2023 An SDE for Modeling SAM: Theory and Insights Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Frank Norbert Proske, Hans Kersting, Aurelien Lucchi

ICML 2023 Controllable Neural Symbolic Regression Tommaso Bendinelli, Luca Biggio, Pierre-Alexandre Kamienny

NeurIPS 2023 Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurelien Lucchi, Thomas Hofmann

ICLR 2023 FIGARO: Controllable Music Generation Using Learned and Expert Features Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hofmann

NeurIPSW 2023 Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization Elior Benarous, Sotiris Anagnostidis, Luca Biggio, Thomas Hofmann

NeurIPSW 2022 Privileged Deep Symbolic Regression Luca Biggio, Bendinelli Tommaso, Pierre-Alexandre Kamienny

NeurIPS 2022 Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurelien Lucchi

NeurIPSW 2021 Empirics on the Expressiveness of Randomized Signature Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto

ICML 2021 Neural Symbolic Regression That Scales Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurelien Lucchi, Giambattista Parascandolo

NeurIPSW 2020 A Seq2Seq Approach to Symbolic Regression Luca Biggio, Tommaso Bendinelli, Aurelien Lucchi, Giambattista Parascandolo