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Found 10 papers, 5 papers with code
Mechanistic Design and Scaling of Hybrid Architectures
The development of deep learning architectures is a resource-demanding process, due to a vast design space, long prototyping times, and high compute costs associated with at-scale model training and evaluation.
Divergent Token Metrics: Measuring degradation to prune away LLM components -- and optimize quantization
Large Language Models (LLMs) have reshaped natural language processing with their impressive capabilities.
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation
The recent popularity of text-to-image diffusion models (DM) can largely be attributed to the intuitive interface they provide to users.
AtMan: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation
Generative transformer models have become increasingly complex, with large numbers of parameters and the ability to process multiple input modalities.
M-VADER: A Model for Diffusion with Multimodal Context
We introduce M-VADER: a diffusion model (DM) for image generation where the output can be specified using arbitrary combinations of images and text.
Speaking Multiple Languages Affects the Moral Bias of Language Models
Do the models capture moral norms from English and impose them on other languages?
Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models
Text-conditioned image generation models have recently achieved astonishing results in image quality and text alignment and are consequently employed in a fast-growing number of applications.
LogicRank: Logic Induced Reranking for Generative Text-to-Image Systems
Text-to-image models have recently achieved remarkable success with seemingly accurate samples in photo-realistic quality.
ILLUME: Rationalizing Vision-Language Models through Human Interactions
Bootstrapping from pre-trained language models has been proven to be an efficient approach for building vision-language models (VLM) for tasks such as image captioning or visual question answering.
Do Multilingual Language Models Capture Differing Moral Norms?
Massively multilingual sentence representations are trained on large corpora of uncurated data, with a very imbalanced proportion of languages included in the training.
