CS 224V

About CS 224V

Computers will transform into effective, personalized, conversational assistants for everybody, including the pre-literate and the non-literate. Commercial chatbots today are notoriously brittle as they are hardcoded to handle a few possible choices of user inputs. Recently introduced large language neural models, such as GPT-3, are remarkably fluent, but they are often erroneous and prone to hallucinations. This course studies how we can tame these neural models into robust, trustworthy, and cost-effective conversational agents across all industries and languages.

Students will learn both the theory and practice with two assignments, and a major open-ended course project of their own design.

Topics include:

• Formal, executable meaning representation for conversational virtual assistants
• Contextual neural semantic parser for translating dialogues into a formal representation.
• Automatic generation of training data for dialogues from high-level schema and API specification with large language models.
• Using large language models in virtual assistants.
• Multilingual, mixed-initiative, multimodal assistants.
• Federated privacy-protecting assistants.