Imagine AI
Tom Yeh, Larissa Schwartz, Cornelius Adejoro, Mohsena Ashraf, Shih-Yu MaTeach AI to the World
| Platform |  | Pricing | Only free issues | Publishes | Daily |
|---|---|---|---|---|---|
| Issues | 46 | Subscribers | Read | imagineai.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
12. Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models
With multimodal models on the rise, Meta recently introduced a sparse multi-modal transformer architecture called 'Mixture-of-Transformers (MoT)' that has a huge impact on reduction of pre-training computational costs.
11. On the Surprising Effectiveness of Attention Transfer for Vision Transformers
This paper illustrates how using only the attention patterns (information flow between tokens) from pre-training is sufficient for models to learn high quality features from scratch. The method demonstrated is called attention transfer.
10. RuAG: Learned-Rule-Augmented Generation For Large Language Models
Combine RAG and Monte Carlo Tree Search (MCTS) and we get RuAG, a very interesting approach to instill data into an LLM. Here is a pdf of my annotated version of the paper, hope this helps you grab the central essence of this cool idea! đź’ˇ ...
9. P-RAG: Progressive Retrieval Augmented Generation For Planning on Embodied Everyday Task
AGI is predicted to be the next frontier in AI and RAG has been incrementally instrumental in enabling this effort. I came across this new approach called P-RAG also called Progressive Retrieval Augmented Generation which leverages the powe...
Authors
The writers behind this newsletter.
Associate Professor of Computer Science
Larissa Schwartz is a PhD student at the ATLAS Institute and a research assistant and member of the Imagine AI Lab in the Department of Computer Science, advised by Dr. Tom Yeh.
I am a PhD Student at CU Boulder. I am interested in research involving AI, children, and parents. Also, I am a proud mother of a baby boy! :)
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