These are unpublished talks. Look under papers for published material. All of these are either PDF (use Adobe Reader, etc.) or PPT (use Microsoft Powerpoint or LibreOffice).
Christopher Manning. 2021. Natural Language Processing has been overrun by large neural language models! What should we make of that? Invited talk at the (last ever!) CUNY Conference on Human Sentence Processing 2021.
Christopher Manning. 2019. Deep Contextual Neural Word Representations: Linguistic Structure Discovery and Efficient Discriminative Training. Invited talk at ElementAI and MILA.
Christopher Manning. 2019. Emergent linguistic structure in deep contextual neural word representations. Invited talk at the Institute for Advanced Study Workshop on Theory of Deep Learning: Where next?
Christopher Manning. 2019. Making the L in VQA Matter: Elevating the Role of Language in Visual Question Answering. Invited talk at the 2019 Visual Question Answering and Dialog Workshop at CVPR 2019.
Christopher Manning and Ruslan Salakhutdinov. 2018. Introductory Overview Lecture: The Deep Learning Revolution. Tutorial at the 2018 Joint Statistical Meetings (JSM).
Christopher Manning. 2018. A Neural Network Model That Can Reason. Invited talk at ICLR 2018. Video on YouTube.
Christopher Manning. 2017. Representations for Language: From Word Embeddings to Sentence Meanings. Talk at Simons Institute for the Theory of Computing workshop on Representation Learning. Video on YouTube.
Christopher Manning. 2017. Deep Learning for Language Understanding – Step 1: Word Vectors. Video on YouTube. Talk given at the 2017 Harker Programming Invitational. A 25 minute talk aimed at high school students (well, bright ones with an advanced math background!).
Here are some other recent videos: Deeply learning the precise meaning of language from the Stanford Data Science Initiative 2016 Retreat, October 11, 2016; Language is Communication; Texts are Knowledge from The Future of Artificial Intelligence event, June 23, 2016.
Christopher Manning. 2016. Natural Language Inference, Reading Comprehension and Deep Learning. Invited talk at SIGIR 2016.
Christopher Manning. 2015. Compositional Deep Learning. Talk at the Workshop on Vector Space Modeling for NLP at NAACL 2015.
Christopher Manning. 2015. Deep Learning for Natural Language Processing. Talk at the 2015 AI Workshop at the Stanford Computer Forum 2015 Annual Affiliates Meeting.
Christopher Manning. 2013. Recursive Deep Learning for Modeling Semantic Compositionality. Invited talk at the Deep Learning Workshop at NIPS 2013.
Christopher Manning. 2013. Texts are Knowledge. Invited talk at Automated Knowledge Base Construction (AKBC) 2013 at CIKM 2013 in San Francisco, October 27-28, 2013.
Richard Socher and Christopher Manning. 2013. Richard Socher, Yoshua Bengio, and Christopher Manning. 2012. Deep Learning for NLP (without magic). Tutorials given at ACL 2012, Jul 2012, Jeju Island, Korea and NAACL 2013, Jun 2012, Atlanta, GA.
Christopher Manning. 2011. Natural Language Processing Tools for the Digital Humanities. Tutorial at Digital Humanities 2011, Jun 2011, Stanford.
Christopher Manning. 2011. Deep Learning of Hierarchical Structure. Invited talk at The Learning Workshop, 2011, Fort Lauderdale, FL.
Christopher Manning. 2007. Learning Language from Distributional Evidence. Talk given at the MIT Workshop on Where Does Syntax Come From?, Oct 2007. You can watch a video.
Christopher Manning. 2006. Robust Local Textual Inference. Talk given at Northwestern University, the University of Chicago, and Stanford University, 2006.
Christopher Manning and Dan Klein, Roger Levy. Natural Language Parsing: Graphs, the A* Algorithm, and Modularity. Talk at University of Toronto, Fall 2003. [Earlier version presented at UC Berkeley CIS Seminar, Johns Hopkins CSLP Seminar, and at Google, Fall 2002.]
Christopher Manning. Opportunities in Natural Language Processing. A general talk on NLP, originally presented at Oracle Corp.
Christopher Manning. Information Pragmatics. Talk at the CSLI Industrial Affiliates Program, 10 November 2000. [Earlier version presented at the Stanford Database Seminar, 29 September 2000.]
Christopher Manning. Probabilistic Models in Computational Linguistics. Talk at the IMA workshop on Mathematical Foundations of Natural Language Modeling, 31 October 2000.
Christopher Manning. Frequencies and Probabilities within the Grammars of Natural Languages. Invited presentation at the Symposium on Mathematical Statistics in Natural Language Analysis at the AAAS 2001 Annual Meeting, San Francisco, 16 February 2001.
Christopher Manning. Linguistics in an age of engineering. A talk on teaching computational linguistics inside linguistics departments, presented at a workshop on computational linguistics within linguistics departments at the LSA Annual Meeting, January 2000.