4 papers
Steered Generation via Gradient Descent on Sparse Features
Sumanta Bhattacharyya, Pedram Rooshenas
Large language models (LLMs) encode a diverse range of linguistic features within their latent representations, which can be harnessed to steer their output toward specific target…
Multimodal ELBO with Diffusion Decoders
Daniel Wesego, Pedram Rooshenas
Multimodal variational autoencoders have demonstrated their ability to learn the relationships between different modalities by mapping them into a latent representation. Their desi…
LLM-Driven Feedback for Enhancing Conceptual Design Learning in Database Systems Courses
Sara Riazi, Pedram Rooshenas
The integration of LLM-generated feedback into educational settings has shown promise in enhancing student learning outcomes. This paper presents a novel LLM-driven system that pro…
Score-Based Multimodal Autoencoder
Daniel Wesego, Pedram Rooshenas
Multimodal Variational Autoencoders (VAEs) represent a promising group of generative models that facilitate the construction of a tractable posterior within the latent space given…