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Found 6 papers, 1 papers with code
Sequential Compositional Generalization in Multimodal Models
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 of complex tasks.
Harnessing Dataset Cartography for Improved Compositional Generalization in Transformers
Neural networks have revolutionized language modeling and excelled in various downstream tasks.
Procedural Reasoning Networks for Understanding Multimodal Procedures
Our model learns to dynamically update entity states in relation to each other while reading the text instructions.
Detecting Cybersecurity Events from Noisy Short Text
In this study, we propose a method that leverages both domain-specific word embeddings and task-specific features to detect cyber security events from tweets.
RecipeQA: A Challenge Dataset for Multimodal Comprehension of Cooking Recipes
With over 36K automatically generated question-answer pairs, we design a set of comprehension and reasoning tasks that require joint understanding of images and text, capturing the temporal flow of events and making sense of procedural knowledge.
