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Found 7 papers, 5 papers with code
Videoshop: Localized Semantic Video Editing with Noise-Extrapolated Diffusion Inversion
We introduce Videoshop, a training-free video editing algorithm for localized semantic edits.
MultiZoo & MultiBench: A Standardized Toolkit for Multimodal Deep Learning
Learning multimodal representations involves integrating information from multiple heterogeneous sources of data.
Model Stealing Attack against Multi-Exit Networks
Compared to traditional neural networks with a single exit, a multi-exit network has multiple exits that allow for early output from intermediate layers of the model, thus bringing significant improvement in computational efficiency while maintaining similar recognition accuracy.
Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework
The recent explosion of interest in multimodal applications has resulted in a wide selection of datasets and methods for representing and integrating information from different modalities.
Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control
Existing techniques for controlling the distribution of generated text only work with quantified distributions, which require pre-defined categories, proportions of the distribution, or an existing corpus following the desired distributions.
High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learning
Many real-world problems are inherently multimodal, from spoken language, gestures, and paralinguistics humans use to communicate, to force, proprioception, and visual sensors on robots.
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning
In order to accelerate progress towards understudied modalities and tasks while ensuring real-world robustness, we release MultiBench, a systematic and unified large-scale benchmark spanning 15 datasets, 10 modalities, 20 prediction tasks, and 6 research areas.
