Christopher Manning
Director, Stanford AI Lab (SAIL) | Thomas M. Siebel Professor, Stanford University
Verified Proof of Work Artifacts
2 items catalogedEach artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Christopher Manning. Every entry undergoes editorial source verification.
Stanford CS224N: Natural Language Processing with Deep Learning
Created and delivered the globally benchmarked Stanford university curriculum educating over one million students online on word vectors, recurrent networks, attention mechanisms, transformers, and modern large language models.
Curriculum must be overhauled annually to keep pace with rapid shifts in foundation model post-training and inference techniques.
GloVe: Global Vectors for Word Representation
Created the GloVe log-bilinear word embedding model that combines the advantages of global matrix factorization and local context window methods, capturing linear substructures and semantic relationships in vector space.
Static word vectors conflate multiple distinct polysemous meanings of words into a single point representation.