9 citations · 10 across the 2 of their papers we have counts for
4 papers
Is there "Secret Sauce'' in Large Language Model Development?
Matthias Mertens, Natalia Fischl-Lanzoni, Neil Thompson
Do leading LLM developers possess a proprietary ``secret sauce'', or is LLM performance driven by scaling up compute? Using training and benchmark data for 809 models released betw…
Neural Scaling Laws in Robotics
Sebastian Sartor, Neil Thompson
Neural scaling laws have driven significant advancements in machine learning, particularly in domains like language modeling and computer vision. However, the exploration of neural…
Large Language Model Routing with Benchmark Datasets
Tal Shnitzer, Anthony Ou, Mírian Silva +5
There is a rapidly growing number of open-source Large Language Models (LLMs) and benchmark datasets to compare them. While some models dominate these benchmarks, no single model t…
The Grand Illusion: The Myth of Software Portability and Implications for ML Progress
Fraser Mince, Dzung Dinh, Jonas Kgomo +2
Pushing the boundaries of machine learning often requires exploring different hardware and software combinations. However, the freedom to experiment across different tooling stacks…