Papers by Xiaochen Hou

2 papers
Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification (2021.naacl-main)

Copied to clipboard

Challenge: Recent work on aspect-level sentiment classification has shown that syntactic information is effective in capturing long-range syntaktic relations that are obscure from the surface form.
Approach: They propose a graph ensemble technique that integrates syntactic structures with GNNs to better leverage syntaktic information in the face of parsing errors.
Outcome: The proposed model outperforms models with single dependency tree and beats other models without adding model parameters.
Towards Comprehensive Patent Approval Predictions:Beyond Traditional Document Classification (2022.acl-long)

Copied to clipboard

Challenge: a new framework for patent approval prediction is proposed to address this problem . novelty scores are based on comparing an application with millions of prior arts .
Approach: They propose a framework that unifies the document classifier with handcrafted features, particularly time-dependent novelty scores.
Outcome: The proposed framework unifies the document classifier with handcrafted features, particularly time-dependent novelty scores.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations