<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Publications | Kyle Williams</title><link>https://kylewilliams.ai/tags/publications/</link><atom:link href="https://kylewilliams.ai/tags/publications/index.xml" rel="self" type="application/rss+xml"/><description>Publications</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Tue, 12 Jul 2022 00:00:00 +0000</lastBuildDate><image><url>https://kylewilliams.ai/media/icon_hu51e05cd49ceb1d79304e966e0d534ed0_15779_512x512_fill_lanczos_center_2.png</url><title>Publications</title><link>https://kylewilliams.ai/tags/publications/</link></image><item><title>Our paper on using medical knowledge graphs to improve abstractive summarization of doctor-patient conversations was presented at EMNLP 2022</title><link>https://kylewilliams.ai/post/emnlp2022/</link><pubDate>Tue, 12 Jul 2022 00:00:00 +0000</pubDate><guid>https://kylewilliams.ai/post/emnlp2022/</guid><description/></item><item><title>I have joined the EmpowerMD in Microsoft Healthcare to work on NLP + Healthcare!</title><link>https://kylewilliams.ai/post/joined-empowemd/</link><pubDate>Fri, 14 Feb 2020 00:00:00 +0000</pubDate><guid>https://kylewilliams.ai/post/joined-empowemd/</guid><description>&lt;p>I have joined the &lt;a href="https://www.microsoft.com/en-us/research/project/empowermd/" target="_blank" rel="noopener">EmpowerMD&lt;/a> within Microsoft Healthcare to work on problems related to NLP + Healthcare. EmpowerMD is a tool that produces clinical notes from doctor-patient conversations.&lt;/p></description></item><item><title>Paper on Zero Shot Intent Classication using LSTMs accepted for publication at INTERSPEECH 2019!</title><link>https://kylewilliams.ai/post/interspeech2019/</link><pubDate>Sun, 14 Jul 2019 01:00:00 +0000</pubDate><guid>https://kylewilliams.ai/post/interspeech2019/</guid><description>&lt;p>Our paper on Zero Shot Intern Classification using LSTMs has been accepted for publication at INTERSPEECH 2019. In this paper we propose an LSTM-based encoder that can be used to map user utterances to dialog intents. We show how the LSTM-based method outperforms a DSSM on this task, both for zero shot and few shot intent classification.&lt;/p></description></item><item><title>Paper on Automatic Task Completion Flows from Web APIs accepted at SIGIR!</title><link>https://kylewilliams.ai/post/sigir2019/</link><pubDate>Sun, 14 Jul 2019 00:00:00 +0000</pubDate><guid>https://kylewilliams.ai/post/sigir2019/</guid><description>&lt;p>Our paper on Automatic Tasks Completion Flows from Web APIs was accepted as a short paper at SIGIR 2019. This paper, co-authored with Seyyed Hadi Hashemi and Imed Zitouni proposed a method for automatically creating task completion flows by chaining together Web APIs. Given a user query, it automatically constructs a flow by chaining together APIs and allowing data to flow from one API to the next. The order in which the APIs are chained is learned by a machine learning model, which generates a set of plans and then scores them by the likelihood of them leading to user satisfaction.&lt;/p></description></item></channel></rss>