1 citations · 1 across the 3 of their papers we have counts for
9 papers
Denoising Hierarchical Representations: Joint Continuous Diffusion for Language Modeling
Mathias Ollu, Nikos Komodakis
Diffusion Language Models (DLMs) hold the promise of order-agnostic, parallel text generation. Recently, continuous diffusion and flow matching models have seen substantial gains,…
Latent-Foresight: End-to-End Learning Predictable Representations for Latent World Models
Efstathios Karypidis, Spyros Gidaris, Nikos Komodakis
Predicting the future evolution of a scene is a fundamental capability for world modeling. Recent work has shown that operating in the feature space of Vision Foundation Models (VF…
Coevolving Representations in Joint Image-Feature Diffusion
Theodoros Kouzelis, Spyros Gidaris, Nikos Komodakis
Joint image-feature generative modeling has recently emerged as an effective strategy for improving diffusion training by coupling low-level VAE latents with high-level semantic fe…
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…
DINO-Foresight: Looking into the Future with DINO
Efstathios Karypidis, Ioannis Kakogeorgiou, Spyros Gidaris +1
Predicting future dynamics is crucial for applications like autonomous driving and robotics, where understanding the environment is key. Existing pixel-level methods are computatio…