440 citations · 674 across the 39 of their papers we have counts for
4 papers · 1 filter
I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token
Roi Cohen, Konstantin Dobler, Eden Biran +1
Large Language Models are known to capture real-world knowledge, allowing them to excel in many downstream tasks. Despite recent advances, these models are still prone to what are…
On the Challenges and Opportunities in Generative AI
Laura Manduchi, Clara Meister, Kushagra Pandey +23
The field of deep generative modeling has grown rapidly in the last few years. With the availability of massive amounts of training data coupled with advances in scalable unsupervi…
Efficient Parallelization Layouts for Large-Scale Distributed Model Training
Johannes Hagemann, Samuel Weinbach, Konstantin Dobler +2
Efficiently training large language models requires parallelizing across hundreds of hardware accelerators and invoking various compute and memory optimizations. When combined, man…
SCALOR: Generative World Models with Scalable Object Representations
Jindong Jiang, Sepehr Janghorbani, Gerard de Melo +1
Scalability in terms of object density in a scene is a primary challenge in unsupervised sequential object-oriented representation learning. Most of the previous models have been s…