---------- Forwarded message ---------
From: Danqi Chen
Date: Mon, Apr 27, 2020 at 12:34 PM
Subject: NLP guest lectures this week
To: ,
Hello everyone,
We will have two guest lectures in my NLP graduate seminar this week from
Jesse Thomason (UW) and Diyi Yang (GaTech). Everyone is welcome to attend
the lectures if you are interested! Please find the details below.
Time: April 28th/30th 1:30-2:50pm
Zoom link: https://princeton.zoom.us/j/767550999
Jesse Thomason - April 28th 1:30-2:50pm
*Title: *Language Grounding with Robots
*Abstract*
We use language to refer to objects like "toast", "plate", and "table" and
to communicate requests such as "Could you make breakfast?" In this talk, I
will present work on computational methods to tie language to physical,
grounded meaning. Robots are an ideal platform for such work because they
can perceive and interact with the world. I will discuss dialog and
learning strategies I have developed to enable robots to learn from their
human partners, similar to how people learn from one another through
interaction. I will present methods enabling robots to understand language
referring expressions like "the heavy, metallic mug", the first work
showing that it is possible to learn to connect words to their perceptual
properties in the visual, tactile, and auditory senses of a physical robot.
I will also present benchmarks and models for translating high-level human
language like "put the toast on the table" that imply latent, intermediate
goals into executable sequences of agent actions with the help of
low-level, step-by-step language instructions.
Diyi Yang - April 30th 1:30-2:50pm
*Title: *Language Understanding in Social Context
*Abstract*
Over the last few decades, natural language processing (NLP) has had
increasing success and produced industrial applications like search, and
personal assistants. Despite being sufficient to enable these applications,
current NLP systems largely ignore the social part of language, e.g., who
says it, in what context, for what goals. My research combines NLP,
linguistics and social science to study how people use language in
different social settings for their social goals, with the implications of
developing systems to facilitate human-human and human-machine
communication. In this talk, I will explain my research from two specific
studies. The first part studies what makes language persuasive by
introducing a semi-supervised neural network to recognize persuasion
strategies in loan requests on crowdfunding platforms, and further designed
neural encoder-decoder systems to automatically transform inappropriately
subjective framing into a neutral point of view. The second focuses on
modeling how people seek and offer support via language in online cancer
support communities and building interventions to support patient
communication. Through these examples, I show how we can accurately and
efficiently build better language technologies for social contexts.
Best,
Danqi
--
*Danqi Chen*
Assistant Professor of Computer Science
Princeton University
http://www.cs.princeton.edu/~danqic/
