activity
20192022
most citedCAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation

89 citations · 181 across the 11 of their papers we have counts for

collaborators

16 papers

cs.IR2022

Hierarchical Conversational Preference Elicitation with Bandit Feedback

Jinhang Zuo, Songwen Hu, Tong Yu +3

The recent advances of conversational recommendations provide a promising way to efficiently elicit users' preferences via conversational interactions. To achieve this, the recomme…

cs.CL202217 cited

Unified Pretraining Framework for Document Understanding

Jiuxiang Gu, Jason Kuen, Vlad I. Morariu +5

Document intelligence automates the extraction of information from documents and supports many business applications. Recent self-supervised learning methods on large-scale unlabel…

cs.CV20217 cited

SelfDoc: Self-Supervised Document Representation Learning

Peizhao Li, Jiuxiang Gu, Jason Kuen +5

We propose SelfDoc, a task-agnostic pre-training framework for document image understanding. Because documents are multimodal and are intended for sequential reading, our framework…

cs.CV20211 cited

RPCL: A Framework for Improving Cross-Domain Detection with Auxiliary Tasks

Kai Li, Curtis Wigington, Chris Tensmeyer +5

Cross-Domain Detection (XDD) aims to train an object detector using labeled image from a source domain but have good performance in the target domain with only unlabeled images. Ex…

cs.CL20212 cited

Edge: Enriching Knowledge Graph Embeddings with External Text

Saed Rezayi, Handong Zhao, Sungchul Kim +3

Knowledge graphs suffer from sparsity which degrades the quality of representations generated by various methods. While there is an abundance of textual information throughout the…

cs.CV2021

ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation

Kai Li, Chang Liu, Handong Zhao +2

This paper studies Semi-Supervised Domain Adaptation (SSDA), a practical yet under-investigated research topic that aims to learn a model of good performance using unlabeled sample…