activity
20182022
most citedDFA-NeRF: Personalized Talking Head Generation via Disentangled Face Attributes Neural Rendering

43 citations · 58 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2022

Revisiting the Roles of "Text" in Text Games

Yi Gu, Shunyu Yao, Chuang Gan +2

Text games present opportunities for natural language understanding (NLU) methods to tackle reinforcement learning (RL) challenges. However, recent work has questioned the necessit…

cs.CL2022

TVShowGuess: Character Comprehension in Stories as Speaker Guessing

Yisi Sang, Xiangyang Mou, Mo Yu +3

We propose a new task for assessing machines' skills of understanding fictional characters in narrative stories. The task, TVShowGuess, builds on the scripts of TV series and takes…

cs.CL20227 cited

Linking Emergent and Natural Languages via Corpus Transfer

Shunyu Yao, Mo Yu, Yang Zhang +3

The study of language emergence aims to understand how human languages are shaped by perceptual grounding and communicative intent. Computational approaches to emergent communicati…

cs.CV202243 cited

DFA-NeRF: Personalized Talking Head Generation via Disentangled Face Attributes Neural Rendering

Shunyu Yao, RuiZhe Zhong, Yichao Yan +2

While recent advances in deep neural networks have made it possible to render high-quality images, generating photo-realistic and personalized talking head remains challenging. Wit…

cs.CL2021

Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents

Shunyu Yao, Karthik Narasimhan, Matthew Hausknecht

Text-based games simulate worlds and interact with players using natural language. Recent work has used them as a testbed for autonomous language-understanding agents, with the mot…

cs.CL20208 cited

Keep CALM and Explore: Language Models for Action Generation in Text-based Games

Shunyu Yao, Rohan Rao, Matthew Hausknecht +1

Text-based games present a unique challenge for autonomous agents to operate in natural language and handle enormous action spaces. In this paper, we propose the Contextual Action…