Month: September 2016

Please join us for the NLP Seminar this Monday (Oct 3) at 3:30pm in 202 South Hall.

Speaker: Sida Wang (Stanford U)

Title: Interactive Language Learning


We introduce 2 parts of the interactive language learning setting. The first is learning from scratch and the second is learning from a community of goal-oriented language users, which is relevant to building adaptive natural language interfaces. The first part is inspired by Wittgenstein’s language games: a human wishes to accomplish some task (e.g., achieving a certain configuration of blocks), but can only communicate with a computer, who performs the actual actions (e.g., removing all red blocks). The computer initially knows nothing about language and therefore must learn it from scratch through interaction, while the human adapts to the computer’s capabilities. We created a game in a blocks world and collected interactions from 100 people playing it.
In the second part (about ongoing work), we explore the setting where a language is supported by a community of people (instead of private to each individual), and the computer has to learn from the aggregate knowledge of a community of goal-oriented language users. We explore how to use additional supervision such as definitions and demonstration


Please join us for the NLP Seminar this Monday (Sept. 19) at 3:30pm in 202 South Hall.
(This is a rescheduling of a talk that was postponed from last semester.)
Speaker: Percy Liang (Stanford)

Title: Learning from Zero


Can we learn if we start with zero examples, either labeled or unlabeled?  This scenario arises in new user-facing systems (such as virtual assistants for new domains), where inputs should come from users, but no users exist until we have a working system, which depends on having training data.  I discuss recent work that circumvent this circular dependence by interleaving user interaction and learning.


Preparatory readings:

Liang, Percy. “Talking to computers in natural language.” XRDS: Crossroads, The ACM Magazine for Students 21.1 (2014): 18-21.
Liang, Percy. “Learning Executable Semantic Parsers for Natural Language Understanding.” arXiv preprint arXiv:1603.06677(2016).