Chinchilla scaling laws
The Chinchilla scaling laws are a set of empirical findings published by DeepMind researchers in 2022 showing that, for a fixed compute budget, a large language model trains most efficiently when its number of…
Large Language Models
Explore language models, how they work, and the techniques used to build applications with them.
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Showing 1-12 of 12 articles
Cross-Model KV Cache Transfer
Cross-model KV cache transfer is an experimental technique for converting the KV cache produced by one large language model into the cache representation expected by another model.
EleutherAI
EleutherAI is a non-profit artificial intelligence research institute that builds and openly releases large language models, datasets, and evaluation tools, and studies their interpretability and alignment.
Guillaume Lample
Guillaume Lample (born 8 October 1990) is a French artificial intelligence researcher and entrepreneur, best known as a senior author of the LLaMA paper produced at Meta AI and as a co-founder and chief…
Jet-Nemotron
Jet-Nemotron is a family of small hybrid-architecture language models released by NVIDIA Research in August 2025.
LLM Evaluation
LLM evaluation is the practice of measuring what a large language model can do, how reliably it does it, and how it behaves under adversarial or high-stakes conditions.
LLM-as-a-Verifier
LLM-as-a-Verifier is a probabilistic verification framework and open-source Python package for scoring and selecting large language model agent trajectories.
Meta AI
Meta AI is the name Meta Platforms uses for two related but distinct things: the company's artificial intelligence research and engineering organization
Nous Research
Nous Research is a New York City-based applied AI research organization and company that builds widely used open-weight language models and decentralized training infrastructure.
RWKV-7 (Goose)
RWKV-7, codenamed Goose, is an attention-free, RNN-style large-language-model architecture introduced in March 2025 that runs inference in linear time with constant memory per token while still training in…
Recursive language model
A recursive language model (RLM) is an inference strategy in which a large language model does not read its input prompt directly.
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models is a landmark research paper published by OpenAI on January 23, 2020 (arXiv:2001.08361) that established that the test loss of a neural language model falls as a smooth…