263 citations · 438 across the 13 of their papers we have counts for
14 papers
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…
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…
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…
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…
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…
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…
VALAN: Vision and Language Agent Navigation
Larry Lansing, Vihan Jain, Harsh Mehta +2
VALAN is a lightweight and scalable software framework for deep reinforcement learning based on the SEED RL architecture. The framework facilitates the development and evaluation o…
RecSim: A Configurable Simulation Platform for Recommender Systems
Eugene Ie, Chih-wei Hsu, Martin Mladenov +5
We propose RecSim, a configurable platform for authoring simulation environments for recommender systems (RSs) that naturally supports sequential interaction with users. RecSim all…
Transferable Representation Learning in Vision-and-Language Navigation
Haoshuo Huang, Vihan Jain, Harsh Mehta +4
Vision-and-Language Navigation (VLN) tasks such as Room-to-Room (R2R) require machine agents to interpret natural language instructions and learn to act in visually realistic envir…
General Evaluation for Instruction Conditioned Navigation using Dynamic Time Warping
Gabriel Ilharco, Vihan Jain, Alexander Ku +2
In instruction conditioned navigation, agents interpret natural language and their surroundings to navigate through an environment. Datasets for studying this task typically contai…
Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation
Vihan Jain, Gabriel Magalhaes, Alexander Ku +3
Advances in learning and representations have reinvigorated work that connects language to other modalities. A particularly exciting direction is Vision-and-Language Navigation(VLN…
Multi-modal Discriminative Model for Vision-and-Language Navigation
Haoshuo Huang, Vihan Jain, Harsh Mehta +2
Vision-and-Language Navigation (VLN) is a natural language grounding task where agents have to interpret natural language instructions in the context of visual scenes in a dynamic…
Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology
Eugene Ie, Vihan Jain, Jing Wang +10
Most practical recommender systems focus on estimating immediate user engagement without considering the long-term effects of recommendations on user behavior. Reinforcement learni…
Wide & Deep Learning for Recommender Systems
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen +13
Generalized linear models with nonlinear feature transformations are widely used for large-scale regression and classification problems with sparse inputs. Memorization of feature…