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Found 8 papers, 3 papers with code
Video Summarization: Towards Entity-Aware Captions
We also release a large-scale dataset, VIEWS (VIdeo NEWS), to support research on this task.
Learning from Children: Improving Image-Caption Pretraining via Curriculum
The difficulty is progressively increased with each new phase by adding one more concept per caption.
IdealGPT: Iteratively Decomposing Vision and Language Reasoning via Large Language Models
Specifically, IdealGPT utilizes an LLM to generate sub-questions, a VLM to provide corresponding sub-answers, and another LLM to reason to achieve the final answer.
Beyond Grounding: Extracting Fine-Grained Event Hierarchies Across Modalities
To support research on this task, we introduce the Multimodal Hierarchical Events (MultiHiEve) dataset.
Generating Rationales in Visual Question Answering
Despite recent advances in Visual QuestionAnswering (VQA), it remains a challenge todetermine how much success can be attributedto sound reasoning and comprehension ability. We seek to investigate this question by propos-ing a new task ofrationale generation.
Progressive Growing of Neural ODEs
Neural Ordinary Differential Equations (NODEs) have proven to be a powerful modeling tool for approximating (interpolation) and forecasting (extrapolation) irregularly sampled time series data.
GANspection
Generative Adversarial Networks (GANs) have been used extensively and quite successfully for unsupervised learning.
Enforcing Reasoning in Visual Commonsense Reasoning
The task of Visual Commonsense Reasoning is extremely challenging in the sense that the model has to not only be able to answer a question given an image, but also be able to learn to reason.
