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Found 6 papers, 3 papers with code
Evaluating Numerical Reasoning in Text-to-Image Models
Text-to-image generative models are capable of producing high-quality images that often faithfully depict concepts described using natural language.
Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings
Human-rated prompt sets are generally small and the reliability of the ratings -- and thereby the prompt set used to compare models -- is not evaluated.
Evaluating Visual Number Discrimination in Deep Neural Networks
The ability to discriminate between large and small quantities is a core aspect of basic numerical competence in both humans and animals.
Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization
Vision-and-language (V&L) models pretrained on large-scale multimodal data have demonstrated strong performance on various tasks such as image captioning and visual question answering (VQA).
Learning to cooperate: Emergent communication in multi-agent navigation
Emergent communication in artificial agents has been studied to understand language evolution, as well as to develop artificial systems that learn to communicate with humans.
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks
Backpropagation through the ODE solver allows each layer to adapt its internal time-step, enabling the network to learn task-relevant time-scales.
Ranked #12 on
Sequential Image Classification
on Sequential MNIST
