---------- 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/