papers

Publications (12)

cs.CV2023

PaLI-3 Vision Language Models: Smaller, Faster, Stronger

Xi Chen, Xiao Wang, Lucas Beyer +16

This paper presents PaLI-3, a smaller, faster, and stronger vision language model (VLM) that compares favorably to similar models that are 10x larger. As part of arriving at this s…

cs.CV2020

Multi-Image Summarization: Textual Summary from a Set of Cohesive Images

Nicholas Trieu, Sebastian Goodman, Pradyumna Narayana +2

Multi-sentence summarization is a well studied problem in NLP, while generating image descriptions for a single image is a well studied problem in Computer Vision. However, for app…

cs.CL2019

Multi-stage Pretraining for Abstractive Summarization

Sebastian Goodman, Zhenzhong Lan, Radu Soricut

Neural models for abstractive summarization tend to achieve the best performance in the presence of highly specialized, summarization specific modeling add-ons such as pointer-gene…

cs.CV2023

PaLI-X: On Scaling up a Multilingual Vision and Language Model

Xi Chen, Josip Djolonga, Piotr Padlewski +40

We present the training recipe and results of scaling up PaLI-X, a multilingual vision and language model, both in terms of size of the components and the breadth of its training t…

cs.CV2023

PaLI: A Jointly-Scaled Multilingual Language-Image Model

Xi Chen, Xiao Wang, Soravit Changpinyo +26

Effective scaling and a flexible task interface enable large language models to excel at many tasks. We present PaLI (Pathways Language and Image model), a model that extends this…

cs.LG2021

Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning

Nan Ding, Xi Chen, Tomer Levinboim +2

Despite recent advances in its theoretical understanding, there still remains a significant gap in the ability of existing PAC-Bayesian theories on meta-learning to explain perform…