Here’s what caught our eye this past week.
Devin
Yi: Open Foundation Models by 01.AI
- The authors introduce the Yi family of models, which include language and multimodal models, that achieve strong scores on popular benchmarks like MMLU and Chatbot Arena.
- Paper.
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
- Google releases Gemini 1.5, which surpasses Gemini 1.0 Ultra’s performance across a broad set of benchmarks.
- Paper
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
- A method that trains LLMs asynchronously and then mixes them together into a Mixture-of-Experts LLM, in order to create LLMs specialized in multiple domains (coding, math).
- Paper
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
- An investigation into the data and architecture choices of what makes a successful LLM.
- Paper
Chronos: Learning the Language of Time Series
- A new framework for understanding time series data to improve forecasting tasks.
- Paper
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