activity
20182022
most citedVALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation

38 citations · 48 across the 7 of their papers we have counts for

collaborators
Showing cs.CLShow all

5 papers · 1 filter

cs.CL2022

Imagination-Augmented Natural Language Understanding

Yujie Lu, Wanrong Zhu, Xin Eric Wang +2

Human brains integrate linguistic and perceptual information simultaneously to understand natural language, and hold the critical ability to render imaginations. Such abilities ena…

cs.CL2020

Towards Understanding Sample Variance in Visually Grounded Language Generation: Evaluations and Observations

Wanrong Zhu, Xin Eric Wang, Pradyumna Narayana +3

A major challenge in visually grounded language generation is to build robust benchmark datasets and models that can generalize well in real-world settings. To do this, it is criti…

cs.CL2020

Multimodal Text Style Transfer for Outdoor Vision-and-Language Navigation

Wanrong Zhu, Xin Eric Wang, Tsu-Jui Fu +5

One of the most challenging topics in Natural Language Processing (NLP) is visually-grounded language understanding and reasoning. Outdoor vision-and-language navigation (VLN) is s…

cs.CL2019

Cross-Lingual Vision-Language Navigation

An Yan, Xin Eric Wang, Jiangtao Feng +2

Commanding a robot to navigate with natural language instructions is a long-term goal for grounded language understanding and robotics. But the dominant language is English, accord…

cs.CL2018

Watch, Listen, and Describe: Globally and Locally Aligned Cross-Modal Attentions for Video Captioning

Xin Wang, Yuan-Fang Wang, William Yang Wang

A major challenge for video captioning is to combine audio and visual cues. Existing multi-modal fusion methods have shown encouraging results in video understanding. However, the…