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Kumar Krishna Agrawal

@kumarkagrawal.bsky.social
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how do we learn? people.eecs.berkeley.edu/~krishna

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Reposted by Kumar Krishna Agrawal
Arna Ghosh @arnaghosh.bsky.social · 31/10/2025
LLMs are trained to compress data by mapping sequences to high-dim representations! How does the complexity of this mapping change across LLM training? How does it relate to the model’s capabilities? 🤔 Announcing our #NeurIPS2025 📄 that dives into this. 🧵below #AIResearch #MachineLearning #LLM
New paper titled "Tracing the Representation Geometry of Language Models from Pretraining to Post-training" by Melody Z Li, Kumar K Agrawal, Arna Ghosh, Komal K Teru, Adam Santoro, Guillaume Lajoie, Blake A Richards.
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Reposted by Kumar Krishna Agrawal
Computational Precision Health @ucjointcph.bsky.social · 10/04/2025
Yala lab's @kumarkagrawal.bsky.social introduces Atlas — a new AI model, inspired by need for better cancer detection, that uses multi-scale attention to analyze large images. At 4K resolution, it’s 7× faster than Vision Transformers and 30% more accurate than MambaVision. buff.ly/6wYexRm
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Reposted by Kumar Krishna Agrawal
Arna Ghosh @arnaghosh.bsky.social · 01/04/2025
Are you training self-supervised/foundation models, and worried if they are learning good representations? We got you covered! 💪 🦖Introducing Reptrix, a #Python library to evaluate representation quality metrics for neural nets: github.com/BARL-SSL/rep... 🧵👇[1/6] #DeepLearning
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Reposted by Kumar Krishna Agrawal
Ian Berlot-Attwell @ianberlot.bsky.social · 15/11/2023
Will multimodal models systematically generalize if trained on enough data? In a controlled VQA setting, we find it’s not data quantity, but data DIVERSITY that matters! 🧵 Joint w/ @ab-carrell.bsky.social @kumarkagrawal.bsky.social Yash Sharma @nsaphra.bsky.social www.cs.toronto.edu/~ianberlot/d...
Authors of the paper "Attribute Diversity Determines the Systematicity Gap in VQA"
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