Summary of When Are 1.58 Bits Enough? a Bottom-up Exploration Of Bitnet Quantization, by Jacob Nielsen et al.
When are 1.58 bits enough? A Bottom-up Exploration of BitNet Quantizationby Jacob Nielsen, Lukas Galke,…
When are 1.58 bits enough? A Bottom-up Exploration of BitNet Quantizationby Jacob Nielsen, Lukas Galke,…
Predictive Digital Twin for Condition Monitoring Using Thermal Imagingby Daniel Menges, Florian Stadtmann, Henrik Jordheim,…
SSSD: Simply-Scalable Speculative Decodingby Michele Marzollo, Jiawei Zhuang, Niklas Roemer, Lorenz K. Müller, Lukas CavigelliFirst…
Streaming Bayes GFlowNetsby Tiago da Silva, Daniel Augusto de Souza, Diego MesquitaFirst submitted to arxiv…
Enhancing Cardiovascular Disease Prediction through Multi-Modal Self-Supervised Learningby Francesco Girlanda, Olga Demler, Bjoern Menze, Neda…
Towards Multi-Modal Mastery: A 4.5B Parameter Truly Multi-Modal Small Language Modelby Ben Koska, Mojmír HorváthFirst…
DNAMite: Interpretable Calibrated Survival Analysis with Discretized Additive Modelsby Mike Van Ness, Billy Block, Madeleine…
The effect of different feature selection methods on models created with XGBoostby Jorge Neyra, Vishal…
Moving Off-the-Grid: Scene-Grounded Video Representationsby Sjoerd van Steenkiste, Daniel Zoran, Yi Yang, Yulia Rubanova, Rishabh…
Quantifying artificial intelligence through algebraic generalizationby Takuya Ito, Murray Campbell, Lior Horesh, Tim Klinger, Parikshit…