Search Results for author:
Found 5 papers, 3 papers with code
Unified-IO 2: Scaling Autoregressive Multimodal Models with Vision, Language, Audio, and Action
We present Unified-IO 2, the first autoregressive multimodal model that is capable of understanding and generating image, text, audio, and action.
Survey on Memory-Augmented Neural Networks: Cognitive Insights to AI Applications
This paper explores Memory-Augmented Neural Networks (MANNs), delving into how they blend human-like memory processes into AI.
Neural Active Learning on Heteroskedastic Distributions
To this end, we demonstrate the catastrophic failure of these active learning algorithms on heteroskedastic distributions and propose a fine-tuning-based approach to mitigate these failures.
MuRIL: Multilingual Representations for Indian Languages
This can be explained by the fact that multilingual language models (LMs) are often trained on 100+ languages together, leading to a small representation of IN languages in their vocabulary and training data.
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy
Adversarial robustness has become a central goal in deep learning, both in the theory and the practice.
