4 citations · 5 across the 6 of their papers we have counts for
6 papers
Sequential Compositional Generalization in Multimodal Models
Semih Yagcioglu, Osman Batur İnce, Aykut Erdem +3
The rise of large-scale multimodal models has paved the pathway for groundbreaking advances in generative modeling and reasoning, unlocking transformative applications in a variety…
PHD: Pixel-Based Language Modeling of Historical Documents
Nadav Borenstein, Phillip Rust, Desmond Elliott +1
The digitisation of historical documents has provided historians with unprecedented research opportunities. Yet, the conventional approach to analysing historical documents involve…
Text Rendering Strategies for Pixel Language Models
Jonas F. Lotz, Elizabeth Salesky, Phillip Rust +1
Pixel-based language models process text rendered as images, which allows them to handle any script, making them a promising approach to open vocabulary language modelling. However…
Evaluating Bias and Fairness in Gender-Neutral Pretrained Vision-and-Language Models
Laura Cabello, Emanuele Bugliarello, Stephanie Brandl +1
Pretrained machine learning models are known to perpetuate and even amplify existing biases in data, which can result in unfair outcomes that ultimately impact user experience. The…
LMCap: Few-shot Multilingual Image Captioning by Retrieval Augmented Language Model Prompting
Rita Ramos, Bruno Martins, Desmond Elliott
Multilingual image captioning has recently been tackled by training with large-scale machine translated data, which is an expensive, noisy, and time-consuming process. Without requ…
Retrieval-augmented Image Captioning
Rita Ramos, Desmond Elliott, Bruno Martins
Inspired by retrieval-augmented language generation and pretrained Vision and Language (V&L) encoders, we present a new approach to image captioning that generates sentences given…