Tapan jain @jainnitk
Analytics Director @GroupM Gurgaon, India Joined September 2009-
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Tapan jain retweeted
We were able to reproduce the strong findings of the HRM paper on ARC-AGI-1. Further, we ran a series of ablation experiments to get to the bottom of what's behind it. Key findings: 1. The HRM model architecture itself (the centerpiece of the paper) is not an important factor.…
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Tapan jain retweeted
This is a fantastic, visually stunning, free introductory book on deep learning. Highly recommended for curious people who want the lay of the land.
Tapan jain retweeted
Just shared a new article on "Building a GPT-Style LLM Classifier From Scratch" (magazine.sebastianraschka.com/p/building-a-g…) along with some insights from some extra experiments that I found super interesting: 1) Do we need to train all layers? 2) Why finetuning the last token, not the first token?…
Tapan jain retweeted
There were a couple of questions regarding Llama 3. Maybe this helps clarifying the differences better:
Tapan jain retweeted
Wondering how GPT and Llama compare under the hood? I built a step-by-step code notebook to break down the key differences: github.com/rasbt/LLMs-fro…
Tapan jain retweeted
Is thats @OpenAI o1 missing secret? @GoogleDeepMind developed a multi-turn chain of thought online reinforcement learning (RL) approach, SCoRe, to improve self-correction using entirely self-generated data. SCoRe achieves state-of-the-art self-correction, improving performance…
Tapan jain retweeted
I haven't had a chance to read yet, but looks like @StefanWager wrote the causal inference book I've always wanted! web.stanford.edu/~swager/causal…
Tapan jain retweeted
If you are interested in a 3-hour deep dive into Causal LLMs in a focused group of 12, welcome to fill in this Google Form forms.gle/paNP66A7cv7koy… for an invite-only session with me and Sergio Garrido. We welcome people who want to (a) learn the basics of Causality and/or LLMs,…
If you are interested in a 3-hour deep dive into Causal LLMs in a focused group of 12, welcome to fill in this Google Form forms.gle/paNP66A7cv7koy… for an invite-only session with me and Sergio Garrido. We welcome people who want to (a) learn the basics of Causality and/or LLMs,…
Tapan jain retweeted
«Linear Algebra and Its Applications» by David & Steven Lay, and Judi McDonald is truly a masterpiece. A textbook teaching Linear Algebra geometrically, application first, with computer exercises and data sets, interactive figures, and projects. 🤩🤩🤩
Tapan jain retweeted
The Transformer's decoder clearly explained 👇🏻
Tapan jain retweeted
For systematically maximizing the performance of deep learning models, really a very comprehensive guide is @Google 's tuning playbook Github repo.
Tapan jain retweeted
The Transformer's encoder clearly explained 👇🏻
Tapan jain retweeted
Large Window-based Mamba UNet for Medical Image Segmentation: Beyond Convolution and Self-attention buff.ly/3WTg6Oq v/ @paperswithcode #HealthTech #AI #MachineLearning #Biotech Cc @ahier @EvanKirstel @kalydeoo @Khulood_Almani @sonu_monika @bimedotcom
Tapan jain retweeted
As im also making a video on model distillation, this is probs one of my favorite paper this week So u basically distill a transformer into a mamba and it can "retain" its original capabilities This performs best on benchmarks compared to any "existing" RNN attn hybrid cope?
As im also making a video on model distillation, this is probs one of my favorite paper this week So u basically distill a transformer into a mamba and it can "retain" its original capabilities This performs best on benchmarks compared to any "existing" RNN attn hybrid cope?
Tapan jain retweeted
In part three of his top-notch series on Mamba state space models, @sascha_kirch turns to use cases focused on images, videos, and time series. buff.ly/3Z6C0R4
Tapan jain retweeted
Here is a good study list if you want a good foundation for working and building with LLMs.
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