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Attention, Please! Revisiting Attentive Probing Through the Lens of Efficiency
Bill Psomas, Dionysis Christopoulos, Eirini Baltzi +6
As fine-tuning becomes impractical at scale, probing is emerging as the preferred evaluation protocol. However, standard linear probing can understate the capability of models whos…
Multi-Token Prediction Needs Registers
Anastasios Gerontopoulos, Spyros Gidaris, Nikos Komodakis
Multi-token prediction has emerged as a promising objective for improving language model pretraining, but its benefits have not consistently generalized to other settings such as f…
Boosting Generative Image Modeling via Joint Image-Feature Synthesis
Theodoros Kouzelis, Efstathios Karypidis, Ioannis Kakogeorgiou +2
Latent diffusion models (LDMs) dominate high-quality image generation, yet integrating representation learning with generative modeling remains a challenge. We introduce a novel ge…
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
Theodoros Kouzelis, Ioannis Kakogeorgiou, Spyros Gidaris +1
Latent generative models have emerged as a leading approach for high-quality image synthesis. These models rely on an autoencoder to compress images into a latent space, followed b…
Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers
Efstathios Karypidis, Ioannis Kakogeorgiou, Spyros Gidaris +1
Semantic future prediction is important for autonomous systems navigating dynamic environments. This paper introduces FUTURIST, a method for multimodal future semantic prediction t…