10 papers
Compression Scaling Laws:Unifying Sparsity and Quantization
Elias Frantar, Utku Evci, Wonpyo Park +2
We investigate how different compression techniques -- such as weight and activation quantization, and weight sparsity -- affect the scaling behavior of large language models (LLMs…
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Petko Georgiev, Ving Ian Lei +1132
In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over…
SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation
Jonathan Roberts, Kai Han, Neil Houlsby +1
Large multimodal models (LMMs) have proven flexible and generalisable across many tasks and fields. Although they have strong potential to aid scientific research, their capabiliti…
PaliGemma: A versatile 3B VLM for transfer
Lucas Beyer, Andreas Steiner, André Susano Pinto +32
PaliGemma is an open Vision-Language Model (VLM) that is based on the SigLIP-So400m vision encoder and the Gemma-2B language model. It is trained to be a versatile and broadly know…
Conditional Diffusion on Web-Scale Image Pairs leads to Diverse Image Variations
Manoj Kumar, Neil Houlsby, Emiel Hoogeboom
Generating image variations, where a model produces variations of an input image while preserving the semantic context has gained increasing attention. Current image variation tech…
Frozen Feature Augmentation for Few-Shot Image Classification
Andreas Bär, Neil Houlsby, Mostafa Dehghani +1
Training a linear classifier or lightweight model on top of pretrained vision model outputs, so-called 'frozen features', leads to impressive performance on a number of downstream…