<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Thesis on</title><link>https://h30306.github.io/blog/tags/thesis/</link><description>Recent content in Thesis on</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>hwork0511@gmail.com (Wei Yi Chung)</managingEditor><webMaster>hwork0511@gmail.com (Wei Yi Chung)</webMaster><copyright>© 2026 Wei Yi Chung</copyright><lastBuildDate>Sun, 06 Feb 2022 00:00:00 +0000</lastBuildDate><atom:link href="https://h30306.github.io/blog/tags/thesis/index.xml" rel="self" type="application/rss+xml"/><item><title>Master's Thesis: Entity Representation Learning and Density Estimation for Coreference Resolution</title><link>https://h30306.github.io/blog/paper/2022-master-thesis-coreference-resolution/</link><pubDate>Sun, 06 Feb 2022 00:00:00 +0000</pubDate><author>hwork0511@gmail.com (Wei Yi Chung)</author><guid>https://h30306.github.io/blog/paper/2022-master-thesis-coreference-resolution/</guid><description>Adding entity representation estimation, within-group density, and between-group density to a SpanBERT coreference model for about +0.9 F1</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://h30306.github.io/blog/paper/2022-master-thesis-coreference-resolution/featured.png"/></item></channel></rss>