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---
layout: page
title: About
weight: 1
---
<center><img src="/lily-logo.png" alt="test image" width="40%" height="40%"></center>
<header class="post-header">
<h2 class="post-title">Language, Information, and Learning at Yale (LILY)</h2>
</header>
<div class = "row">
<div class = "">
<p align="left"> <div class="left"> This is the website for the LILY (Language, Information, and Learning at Yale) Lab at the Department of Computer Science, Yale University.</div> </p>
</div>
</div>
<div class = "row">
<div class = "">
<p align="left"> <div class="left"> <i><b>NEWS</b></i> </div> </p>
<ul>
<li><b><font color="red">Oct 2022</font></b> We have 8 papers accepted to EMNLP 2022, including 7 in the main session and 1 in Findings! Stay tuned for the links.
<li><b><font color="red">July 2022</font></b> Check out our papers at <a href="https://aclanthology.org/events/naacl-2022">NAACL 2022</a>.
<li><b><font color="red">May 2022</font></b> Congratulations to Yixin for winning an "outstanding demo paper" at ACL 2022! Check it out <a href="https://www.2022.aclweb.org/best-demo-paper-award">here</a>!
<li><b><font color="red">Apr 2022</font></b> Our new toolkit <a href="https://github.com/Yale-LILY/EHRKit-2022">EHRKit</a> is released. Check it out!
<li><b><font color="red">Apr 2022</font></b> Three papers accepted to NAACL 2022! KAT: A Knowledge Augmented Transformer for Vision-and-Language, Investigating Crowdsourcing Protocols for Evaluating the Factual Consistency of Summaries, and CONFIT: Toward Faithful Dialogue Summarization with Linguistically-Informed Contrastive Fine-tuning!
<li><b><font color="red">Feb 2022</font></b> Four papers accepted to ACL 2022! BRIO: Bringing Order to Abstractive Summarization, DYLE: Dynamic Latent Extraction for Abstractive Long-Input Summarization, Summ^N: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents, and Variational Graph Autoencoding as Cheap Supervision for AMR Coreference Resolution!
<li><b><font color="red">Feb 2022</font></b> The Github repository for BRIO is <a href="https://github.com/yixinL7/BRIO">released</a>. Check it out!
<li><b><font color="red">Nov 2021</font></b> Our SummerTime repository is <a href="https://pypi.org/project/summertime/">online</a> and pip-installable now. Check it out!
<li><b><font color="red">Aug 2021</font></b> Three papers accepted to EMNLP! Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalization, An Exploratory Study on Long Dialogue Summarization: What Works and What’s Next, and SummerTime: Text Summarization Toolkit for Non-experts!
<li><b><font color="red">Jun 2021</font></b> One paper accepted to TACL! FeTaQA: Free-form Table Question Answering!
<li><b><font color="red">Jun 2021</font></b> A new release of <a href="https://aan.how">AAN</a>, our NLP search endine, is available. More than 20,000 resources are currently indexed there. We have a <a href="https://medium.com/lily-lab/aan-how-aan-new-version-release-b4eaad7e026c">blog post</a> with more details.
<li><b><font color="red">Jun 2021</font></b> A new release of <a href="https://github.com/Yale-LILY/LectureBank">LectureBank</a> is now available.
<li><b><font color="red">Jun 2021</font></b> A new release of <a href="https://github.com/Yale-LILY/TutorialBank">TutorialBank</a> is now available.
<li><b><font color="red">May 2021</font></b> Three papers accepted to ACL 2021! ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining, Unsupervised Cross-Domain Prerequisite Chain Learning using Variational Graph Autoencoders, and BookSum: A Collection of Datasets for Long-form Narrative Summarization!
<li><b><font color="red">Apr 2021</font></b> Our SummEval repository is <a href="https://pypi.org/project/summ-eval/">online</a> and pip-installable now. Check it out!
<li><b><font color="red">Apr 2021</font></b> One <a href="https://www.nature.com/articles/s41746-021-00437-0">paper</a> published at npj digital medicine: COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization!
<li><b><font color="red">Apr 2021</font></b> Our new dataset FeTaQA: Free-form Table Question Answering has been released <a href="https://github.com/Yale-LILY/FeTaQA">online</a> now! Check it out!
<li><b><font color="red">Apr 2021</font></b> We updated <a href="aan.how">aan.how</a>, which now has over 16k manually-curated resources on NLP and related topics!
<li><b><font color="red">Apr 2021</font></b> Khera Awarded Career Development Grant from National Heart, Lung, and Blood Institute!
<li><b><font color="red">Mar 2021</font></b> Three papers accepted to NAACL! Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation, DART: Open-Domain Structured Data Record to Text Generation, and QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization!
<li><b><font color="red">Mar 2021</font></b> Two papers accepted to ICLR! GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing and SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing!
<li><b><font color="red">Mar 2021</font></b> Tao Yu has successfully defended his PhD dissertation on semantic parsing for natural language interfaces. Congratulations to Dr. Yu!
<li><b><font color="red">Feb 2021</font></b> Alex Fabbri has successfully defended his PhD dissertation on natural language processing for text summarization. Congratulations to Dr. Fabbri!
</ul>
<p align="left"> <div class="left"> The LILY Lab started in Spring 2017 with Professor <a href="http://www.cs.yale.edu/homes/radev/"> Dragomir Radev </a> joining Yale University. Our interests include:</div> </p>
<ul>
<li> Natural Language Processing </li>
<ul>
<li> Summarization </li>
<li> Semantic Parsing </li>
<li> Question Answering </li>
<li> Dialogue Systems </li>
<li> Information Retrieval </li>
<li> Graph Methods for NLP and IR </li>
<li> Logical Reasoning </li>
<li> Language Grounding </li>
<li> Natural Language Generation </li>
<li> NLP for Database Access </li>
<li> NLP for Code Generation </li>
</ul>
<li> Machine Learning </li>
<ul>
<li> Neural Networks </li>
<li> Semi-Supervised Learning </li>
<li> Multimodal Machine Learning </li>
</ul>
</ul>
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<ul>
<li> Natural Language Processing </li>
<ul>
<li> Information Retrieval </li>
<li> Summarization </li>
<li> Multilingual Parsing </li>
<li> Dialogue Systems </li>
<li> Question Answering </li>
<li> Humor Detection </li>
</ul>
<li> Machine Learning </li>
<ul>
<li> Neural Networks </li>
<li> Semi-supervised Learning </li>
</ul>
</ul>
-->
</div>
</div>