Discover CoCoMix by Meta AI – a new approach for LLM pretraining using Continuous Concept Mixing, enriching word tokens with latent concepts!
CoCoMix by Meta AI – The Future of LLMs Pretraining? Read More »
Discover s1: a simple yet powerful approach to test-time scaling for LLMs, rivaling o1-preivew with just 1k samples!
s1: Simple Test-Time Scaling – Can 1k Samples Rival o1-Preview? Read More »
Dive into the groundbreaking DeepSeek-R1 research paper, introduces open-source reasoning models that rivals the performance OpenAI’s o1!
DeepSeek-R1 Paper Explained – A New RL LLMs Era in AI? Read More »
Dive into Titans, a new AI architecture by Google, showing promising results comparing to Transformers! Paving the way for a new era in AI?
Titans by Google: The Era of AI After Transformers? Read More »
Discover how System 2 thinking through Monte Carlo Tree Search enables rStar-Math to rival OpenAI’s o1 in math, using Small Language Models!
rStar-Math by Microsoft: Can SLMs Beat OpenAI o1 in Math? Read More »
Explore Meta’s Large Concept Models (LCMs) - an AI model that processes concepts instead of tokens. Can it become the next LLM architecture?
Large Concept Models (LCMs) by Meta: The Era of AI After LLMs? Read More »
Explore Byte Latent Transformer (BLT) by Meta AI: A tokenizer-free LLM that scales better than tokenization-based LLMs
Byte Latent Transformer (BLT) by Meta AI: A Tokenizer-free LLM Revolution Read More »
Discover how Meta AI’s Chain of Continuous Thought (Coconut) empowers large language models (LLMs) to reason in their own language.
Coconut by Meta AI – Better LLM Reasoning With Chain of CONTINUOUS Thought? Read More »
Discover NVIDIA’s Hymba model that combines Transformers and State Space Models for state-of-the-art performance in small language models
Hymba by NVIDIA: A Hybrid Mamba-Transformer Language Model Read More »
Dive into Nvidia’s LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models, a LLM which was adapted to understand 3D objects.
LLaMA-Mesh by Nvidia: LLM for 3D Mesh Generation Read More »
