6 papers
Subliminal Clocks: Latent Time Modelling in Diffusion Language Models
Maximo Rulli, Maximo Eduardo Rulli, Thomas Vaitses Fontanari +11
Diffusion Language Models (DLMs) have recently emerged as a promising alternative to autoregressive models. Unlike standard diffusion-based approaches, DLMs are not explicitly cond…
Language Models are Injective and Hence Invertible
Giorgos Nikolaou, Tommaso Mencattini, Donato Crisostomi +3
Transformer components such as non-linear activations and normalization are inherently non-injective, suggesting that different inputs could map to the same output and prevent exac…
Escaping Plato's Cave: Towards the Alignment of 3D and Text Latent Spaces
Souhail Hadgi, Luca Moschella, Andrea Santilli +5
Recent works have shown that, when trained at scale, uni-modal 2D vision and text encoders converge to learned features that share remarkable structural properties, despite arising…
Mergenetic: a Simple Evolutionary Model Merging Library
Adrian Robert Minut, Tommaso Mencattini, Andrea Santilli +2
Model merging allows combining the capabilities of existing models into a new one - post hoc, without additional training. This has made it increasingly popular thanks to its low c…
MERGE: Efficient Evolutionary Merging on Consumer-grade GPUs
Tommaso Mencattini, Adrian Robert Minut, Donato Crisostomi +2
Evolutionary model merging enables the creation of high-performing multi-task models but remains computationally prohibitive for consumer hardware. We introduce MERGE, an effic…
Preserving Privacy in Large Language Models: A Survey on Current Threats and Solutions
Michele Miranda, Elena Sofia Ruzzetti, Andrea Santilli +3
Large Language Models (LLMs) represent a significant advancement in artificial intelligence, finding applications across various domains. However, their reliance on massive interne…