activity
20162021
most citedWide & Deep Learning for Recommender Systems

263 citations · 401 across the 9 of their papers we have counts for

collaborators

14 papers

cs.LG20219 cited

RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems

Martin Mladenov, Chih-Wei Hsu, Vihan Jain +7

The development of recommender systems that optimize multi-turn interaction with users, and model the interactions of different agents (e.g., users, content providers, vendors) in…

cs.AI202111 cited

On the Evaluation of Vision-and-Language Navigation Instructions

Ming Zhao, Peter Anderson, Vihan Jain +4

Vision-and-Language Navigation wayfinding agents can be enhanced by exploiting automatically generated navigation instructions. However, existing instruction generators have not be…

cs.CV202020 cited

A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus

Bowen Zhang, Hexiang Hu, Joonseok Lee +5

Identifying a short segment in a long video that semantically matches a text query is a challenging task that has important application potentials in language-based video search, b…

cs.CV2020

Learning to Represent Image and Text with Denotation Graph

Bowen Zhang, Hexiang Hu, Vihan Jain +2

Learning to fuse vision and language information and representing them is an important research problem with many applications. Recent progresses have leveraged the ideas of pre-tr…

cs.AI20208 cited

BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps

Wang Zhu, Hexiang Hu, Jiacheng Chen +4

Learning to follow instructions is of fundamental importance to autonomous agents for vision-and-language navigation (VLN). In this paper, we study how an agent can navigate long p…

cs.AI2020

Environment-agnostic Multitask Learning for Natural Language Grounded Navigation

Xin Eric Wang, Vihan Jain, Eugene Ie +3

Recent research efforts enable study for natural language grounded navigation in photo-realistic environments, e.g., following natural language instructions or dialog. However, exi…