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Large Language Models (LLMs) are increasingly applied to critical domains such as medical report generation, where accuracy and trust are essential. Evaluating the quality of generated text is non-trivial: surface word matches may miss key semantic errors, while semantic metrics may overlook…
Paper: https://research.trychroma.com/context-rotAbstract:Large Language Models (LLMs) are typically presumed to process context uniformly—that is, the model...
Paper: https://arxiv.org/abs/2507.02092Code: https://github.com/alexiglad/EBTWebsite: https://energy-based-transformers.github.io/Abstract:Inference-time com...
An in-depth look at Anthropic's Transformer Circuit Blog PostPart 1 here: https://youtu.be/mU3g2YPKlsADiscord here: https;//ykilcher.com/discordhttps://trans...
An in-depth look at Anthropic's Transformer Circuit Blog Posthttps://transformer-circuits.pub/2025/attribution-graphs/biology.htmlAbstract:We investigate the...
#deepseek #llm #grpoGRPO is one of the core advancements used in Deepseek-R1, but was introduced already last year in this paper that uses a combination of n...
Convolutional Variational Autoencoder (CVAE) to generate synthetic tractography-based bundle templates from small population data.
https://ykilcher.com/discordLinks:TabNine Code Completion (Referral): http://bit.ly/tabnine-yannickYouTube: https://www.youtube.com/c/yannickilcherTwitter: h...
Implicit neural representations (INRs) are a class of neural networks that represent a function instead of solving a task. Their main advantage is that they can represent signals continuously in space, which is useful for tasks such as 3D reconstruction, image generation, and physical simulation.
In this tutorial, we use Gradio to examine adversarial attacks and their potential for misdirecting models towards making inaccurate predictions.
Dive deep to understand the architecture of high-performance H100 GPU which has marked a significant advancement in the field of AI.
Learn about a variety of techniques used to keep deep learning NLP models secure.
Engineering and running experiments are a key component of most PhDs in AI. While there are plenty of more theoretical topics that are often limited to smaller scale experimentation, the trend has definitely been to scale up models, datasets and experiments.
Is Attention all you need? Mamba, a novel AI model based on State Space Models (SSMs), emerges as a formidable alternative to the widely used Transformer models, addressing their inefficiency in processing long sequences.
Posted by Nishant Jain, Pre-doctoral Researcher, and Pradeep Shenoy, Research Scientist, Google Research The constantly changing nature of the worl...
Posted by Rishabh Tiwari, Pre-doctoral Researcher, and Pradeep Shenoy, Research Scientist, Google Research Machine learning models in the real worl...
Posted by Manish Gupta, Staff Software Engineer, Google Research AI-driven technologies are weaving themselves into the fabric of our daily routine...
Posted by Ameya Velingker, Research Scientist, Google Research, and Balaji Venkatachalam, Software Engineer, Google Graphs, in which objects and th...
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