1 citations · 1 across the 4 of their papers we have counts for
4 papers
Discovering Meaningful Units with Visually Grounded Semantics from Image Captions
Melika Behjati, James Henderson
Fine-grained knowledge is crucial for vision-language models to obtain a better understanding of the real world. While there has been work trying to acquire this kind of knowledge…
GABInsight: Exploring Gender-Activity Binding Bias in Vision-Language Models
Ali Abdollahi, Mahdi Ghaznavi, Mohammad Reza Karimi Nejad +6
Vision-language models (VLMs) are intensively used in many downstream tasks, including those requiring assessments of individuals appearing in the images. While VLMs perform well i…
Learning to Abstract with Nonparametric Variational Information Bottleneck
Melika Behjati, Fabio Fehr, James Henderson
Learned representations at the level of characters, sub-words, words and sentences, have each contributed to advances in understanding different NLP tasks and linguistic phenomena.…
Inducing Meaningful Units from Character Sequences with Dynamic Capacity Slot Attention
Melika Behjati, James Henderson
Characters do not convey meaning, but sequences of characters do. We propose an unsupervised distributional method to learn the abstract meaningful units in a sequence of character…