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Found 5 papers, 1 papers with code
Categorical Deep Learning: An Algebraic Theory of Architectures
We present our position on the elusive quest for a general-purpose framework for specifying and studying deep learning architectures.
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning
As a result, it is usually necessary to reproduce the experiments from scratch, which can be time-consuming and error-prone.
Scalable Training of Language Models using JAX pjit and TPUv4
Modern large language models require distributed training strategies due to their size.
No News is Good News: A Critique of the One Billion Word Benchmark
The One Billion Word Benchmark is a dataset derived from the WMT 2011 News Crawl, commonly used to measure language modeling ability in natural language processing.
Mitigating harm in language models with conditional-likelihood filtration
Language models trained on large-scale unfiltered datasets curated from the open web acquire systemic biases, prejudices, and harmful views from their training data.
