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<!DOCTYPE html>
<html lang="en">
<head>
<title>NAACL 2025 Tutorial: Learning Language through Grounding</title>
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content="Language Grounding, Machine Learning, Computational Linguistics, Natural Language Processing, Computer Science, Cognitive Science">
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<a href="#bibtex">BibTeX</a>
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<div class="ftsubheader">
<a href="#references">References</a>
</div>
<div class="ftsubheader">
<a href="#materials">Materials</a>
</div>
<div class="ftsubheader">
<a href="#main">Home</a>
</div>
</div>
</header>
<div id="main">
<div class="main-content">
<div id="main-content-container" class="container">
<div class="row">
<div class="col-sm-12 col-md-12">
<div id="main-info-container">
<div class="col-name">
<span class="name-with-icons">
<div class="name" style="font-weight:bold;">Learning Language through Grounding
</div>
<div class="name" style="padding-top:5px; font-size: 22px; vertical-align: bottom;">
(NAACL 2025 Tutorial)</div>
</span>
<p class="text">
<i>Grounding</i> has been a long-standing concept in natural language processing
(NLP) and computational linguistics (CL).
This tutorial provides a historical overview and introduces recent advances in
learning language through grounding, with a particular emphasis on the latter.
We will begin by tracing the history of grounding and presenting a unified
perspective on the term.
In Parts II to IV, we will delve into recent progress in learning lexical semantics,
syntax, and complex meanings through various forms of grounding.
We will conclude by discussing future directions and open challenges, particularly
those related to the growing trend of large language models and scaling.
</p>
<div class="name" style="padding-top:5px; font-size: 22px; vertical-align: bottom;">
Tutorial Instructors</div>
<br>
</div>
</div>
</div>
<div class="col-sm-12 col-md-4 col-avatar"
style="display: flex; align-items: center; flex-direction: column; text-align: center;">
<img src="static/img/freda.jpg" class="avatar"
style="width: 100px; height: 100px; border-radius: 50%;" />
<h6 class="subtitle" style="margin: 5px 0;">
<a href="https://cs.uwaterloo.ca/~fhs/">Freda Shi</a>
<a href="https://scholar.google.com/citations?hl=en&user=jkDd-3QAAAAJ" target="blank"><i
class="ai ai-google-scholar ai-lg"></i></a>
<a href="https://twitter.com/fredahshi" target="blank"><i class="fa fa-twitter"></i></a>
<a href="mailto:fhs@uwaterloo.ca"><i class="fa fa-envelope-o"></i></a>
</h6>
<h6 class="subtitle" style="margin: 2;">
<i>University of Waterloo & Vector Institute, Canada CIFAR AI Chair</i>
</h6>
</div>
<div class="col-sm-12 col-md-4 col-avatar"
style="display: flex; align-items: center; flex-direction: column; text-align: center;">
<img src="static/img/martin.jpg" class="avatar"
style="width: 100px; height: 100px; border-radius: 50%;" />
<h6 class="subtitle" style="margin: 5px 0;">
<a href="https://mars-tin.github.io/">Ziqiao Ma</a>
<a href="https://scholar.google.com/citations?user=WbybssYAAAAJ&hl=en" target="blank"><i
class="ai ai-google-scholar ai-lg"></i></a>
<a href="https://twitter.com/ziqiao_ma" target="blank"><i class="fa fa-twitter"></i></a>
<a href="mailto:marstin@umich.edu"><i class="fa fa-envelope-o"></i></a>
</h6>
<h6 class="subtitle" style="margin: 2;">
<i>University of Michigan</i>
</h6>
</div>
<div class="col-sm-12 col-md-4 col-avatar"
style="display: flex; align-items: center; flex-direction: column; text-align: center;">
<img src="static/img/jiayuan.jpg" class="avatar"
style="width: 100px; height: 100px; border-radius: 50%;" />
<h6 class="subtitle" style="margin: 5px 0;">
<a href="https://jiayuanm.com/">Jiayuan Mao</a>
<a href="https://scholar.google.com/citations?user=-xaOIZIAAAAJ&hl=en" target="blank"><i
class="ai ai-google-scholar ai-lg"></i></a>
<a href="https://twitter.com/maojiayuan" target="blank"><i class="fa fa-twitter"></i></a>
<a href="mailto:jiayuanm@mit.edu"><i class="fa fa-envelope-o"></i></a>
</h6>
<h6 class="subtitle" style="margin: 2;">
<i>Massachusetts Institute of Technology</i>
</h6>
</div>
<div class="col-sm-12 col-md-4 col-avatar"
style="display: flex; align-items: center; flex-direction: column; text-align: center;">
<img src="static/img/parisa.png" class="avatar"
style="width: 100px; height: 100px; border-radius: 50%;" />
<h6 class="subtitle" style="margin: 5px 0;">
<a href="https://www.cse.msu.edu/~kordjams/">Parisa Kordjamshidi</a>
<a href="https://scholar.google.com/citations?user=Ugo3NGgAAAAJ&hl=en" target="blank"><i
class="ai ai-google-scholar ai-lg"></i></a>
<a href="https://twitter.com/Kordjamshidi" target="blank"><i class="fa fa-twitter"></i></a>
<a href="mailto:kordjams@msu.edu"><i class="fa fa-envelope-o"></i></a>
</h6>
<h6 class="subtitle" style="margin: 2;">
<i>Michigan State University</i>
</h6>
</div>
<div class="col-sm-12 col-md-4 col-avatar"
style="display: flex; align-items: center; flex-direction: column; text-align: center;">
<img src="static/img/joyce.jpg" class="avatar"
style="width: 100px; height: 100px; border-radius: 50%;" />
<h6 class="subtitle" style="margin: 5px 0;">
<a href="https://web.eecs.umich.edu/~chaijy/">Joyce Chai</a>
<a href="mailto:chaijy@umich.edu"><i class="fa fa-envelope-o"></i></a>
</h6>
<h6 class="subtitle" style="margin: 2;">
<i>University of Michigan</i>
</h6>
</div>
</div>
</div>
</div>
</div>
<div class="main-content">
<div class="main-more-container" id="materials">
<div class="main-bio-container">
<h3 class="subtitle" style="margin-top:25px">Materials (180 minutes)</h3>
<h4 class="subtitle" style="margin-top:25px">
Part I (15 minutes): Introduction to grounding.
[Slides] [Video]
</h4>
<h5 class="subtitle">Presenter: Freda Shi</h5>
<p style="margin-bottom:5px;">
We will review the history of grounding, and introduce the unified definition of grounding.
In particular, grounding, in this tutorial, refers to processing the primary data with supervision
from another source, where the two sources of data have positive mutual information.
We will exemplify the definition through connection to existing work such as visual grounding,
acoustic grounding, factual grounding, and cross-lingual grounding.
</p>
<p style="margin-bottom:5px;">
We refer to <a href="https://spatial-language-tutorial.github.io/">NAACL 2024 Tutorial 6</a> on
spatial and temporal grounding,
<a href="https://aclanthology.org/2020.acl-tutorials.3/">ACL 2020 Tutorial 5</a> on
building common ground through communication, and
<a href="https://videolectures.net/videos/aaai2013_mooney_language_learning">AAAI 2013 Keynote</a>
for early work on grounded language learning.
</p>
<h4 class="subtitle" style="margin-top:25px">
Part II (25 minutes): Learning lexicons through grounding.
[Slides] [Video]
</h4>
<h5 class="subtitle">Presenter: Martin Ziqiao Ma</h5>
<p style="margin-bottom:5px;">
Word acquisition is a core challenge in both cognitive science and robotics.
Recent advances in neural networks and multimodal machine learning have enabled efforts to
ground the meanings of written and spoken words in visual signals.
In this talk, we will explore research on grounding noun and verb meanings through changes in the physical
world.
We will also briefly discuss extensions of lexicon grounding beyond the visual modality,
as well as approaches to bootstrapping grounded word acquisition through meta-learning.
</p>
<p style="margin-bottom:5px;">
In the first 10 minutes, we will introduce the background and focus on recent advances in the
remaining time.
Work on vision-language models, learning lexical semantics through interaction or
learning lexicon to compose sentence-level meanings will be deferred to Part IV.
</p>
<h4 class="subtitle" style="margin-top:25px">
Part III (25 minutes): Learning syntax through grounding.
[Slides] [Video]
</h4>
<h5 class="subtitle">Presenter: Freda Shi</h5>
<p style="margin-bottom:5px;">
Constituency parses of sentences can be learned by grounding to visual signals.
Follow-up work has demonstrated the effectiveness of such visually grounded systems on learning
variants of constituency and dependency grammars.
On another line, <i>word alignment</i>, based cross-lingual transfer can also be considered as an
instantiation of learning syntax through cross-lingual grounding,
where the text in the target language(s) is grounded to existing knowledge in the source
language(s).
</p>
<p style="margin-bottom:5px;">
A brief introduction of related syntactic knowledge, such as constituency, dependency, and
combinatory categorial grammars,
will be presented in the first 10 minutes of this part to help the audience better understand the
content.
We will focus on recent approaches to learning syntax through visual grounding and cross-lingual
grounding in the rest of the time.
Efforts on joint learning of syntax and semantics will be delivered in Part IV.
</p>
<!-- <h4 class="subtitle" style="margin-top:25px">
Coffee Break (10 minutes)
</h4> -->
<h4 class="subtitle" style="margin-top:25px">
Part IV (100 minutes): Learning complex meanings (semantics and pragmatics) through grounding.
</h4>
<h5 class="subtitle" style="margin-top:25px">
Part IV-1 (25 minutes): Learning concepts through grounding.
[Slides] [Video]
</h5>
<h5 class="subtitle">Presenter: Jiayuan Mao</h5>
<p style="margin-bottom:5px;">
Grounded lexicon learning and grounded syntax learning come together to enable the formation of complex,
compositional grounded concepts.
Lexicon learning maps individual words to grounded perceptual or executable representations,
while syntax learning governs how these word-level representations are composed into structured meanings.
By integrating both, models can not only learn visual or perceptual concepts from language
but also generalize to novel compositions, facilitating systematic and interpretable understanding
of grounded semantics across diverse domains.
</p>
<h5 class="subtitle" style="margin-top:25px">
Part IV-2 (25 minutes): Grounding language to world representations: The case of space.
[Slides] [Video]
</h5>
<h5 class="subtitle">Presenter: Parisa Kordjamshidi</h5>
<p style="margin-bottom:5px;">
We cover how spatial semantics are represented, the available datasets and annotations,
and the connection between information extraction models, qualitative spatial reasoning,
and end-to-end deep learning approaches.
We review recent large language models for spatial language comprehension, their evaluation,
and the key limitations and challenges in this area.
We clarify the role of spatial language in downstream applications,
highlighting tasks such as grounding language in the visual world for navigation, wayfinding agents,
human-machine interaction, and situated dialogue systems.
</p>
<h5 class="subtitle" style="margin-top:25px">
Part IV-3 (25 minutes): Scaling vision-language models with grounding.
[Slides] [Video]
</h5>
<h5 class="subtitle">Presenter: Martin Ziqiao Ma</h5>
<p style="margin-bottom:5px;">
While modern vision-language models (VLMs) have made remarkable progress,
achieving fine-grained grounding of linguistic units to perceptual referents remains an open challenge.
We will review recent advances in mechanistically grounded VLMs, spanning both encoder-based and generative
ones.
We highlight how these models offer more detailed perceptual understanding and greater interpretability,
providing new insights into the mechanisms underlying grounded language acquisition.
</p>
<h5 class="subtitle" style="margin-top:25px">
Part IV-4 (25 minutes): Learning pragmatics through grounding.
[Slides] [Video]
</h5>
<h5 class="subtitle">Presenter: Joyce Chai</h5>
<p style="margin-bottom:5px;">
Grounded interaction provides a powerful source of supervision for language learning,
connecting linguistic expressions directly to perception and action.
Beyond mapping words to perceptual referents, successful communication requires models
to interpret language in context — leveraging shared goals, conventions, and the visual and embodied
environment.
We discuss research on grounded settings and pragmatic modeling, analyzing how grounding
in physical and social contexts shapes linguistic meaning, and how task goals, environmental structure,
and communicative affordances enrich the process of language grounding.
</p>
<h4 class="subtitle" style="margin-top:25px">
Part V (15 minutes): Future directions and open problems.
[Slides] [Video]
</h4>
<h5 class="subtitle">Presenter: Freda Shi</h5>
<p style="margin-bottom:5px;">
A key discussion for future directions centers around whether grounding should emerge naturally from
scaling models or whether we should enforce grounded supervision to achieve more efficient learning.
Additionally, the scope of grounding can be broadened beyond traditional modalities,
incorporating touch, olfaction, non-human sensors, video and temporal data, 3D environments,
proprioception, episodic experiences, and even other forms of meta-cognition.
</p>
</div>
</div>
<div class="main-more-container" id="references">
<div id="main-pub-container">
<h4 class="subtitle">References
<span style="padding-left: 30px;">
<a id="publication-by-selected" href="javascript:;" , onClick="publicationBySelected();"
style="font-size:18px;">show selected</a> /
<a id="publication-by-topic" href="javascript:;" , onClick="publicationByTopic();"
style="font-size:18px;">show all by topic</a>
</span>
</h4>
<p class="subtitle-aux">
<!--<span class="bold">Grounding for:</span>-->
<a href="#topic-overview" onClick="return publicationByTopicSpecific(this)"
data-topic="overview">Overview</a>
<br>
<a href="#topic-lexicon" onClick="return publicationByTopicSpecific(this)" data-topic="lexicon">Lexicon
Learning</a> /
<a href="#topic-syntax" onClick="return publicationByTopicSpecific(this)" data-topic="syntax">Syntax
Learning</a> /
<a href="#topic-semantics" onClick="return publicationByTopicSpecific(this)"
data-topic="semantics">Semantics Learning</a> /
<a href="#topic-pragmatics" onClick="return publicationByTopicSpecific(this)"
data-topic="pragmatics">Pragmatics Learning</a>
<br>
<a href="#topic-crossmodal" onClick="return publicationByTopicSpecific(this)"
data-topic="crossmodal">Crossmodal Grounding</a> /
<a href="#topic-crosslingual" onClick="return publicationByTopicSpecific(this)"
data-topic="crosslingual">Crosslingual Grounding</a> /
<a href="#topic-epstemic" onClick="return publicationByTopicSpecific(this)" data-topic="epistemic">Epistemic
Grounding</a> /
<a href="#topic-interaction" onClick="return publicationByTopicSpecific(this)"
data-topic="interaction">Interactive Grounding</a>
<br>
</p>
<div id="main-pub-card-container" class="activated hide">
<!--Papers Come Here-->
</div>
</div>
<div class="main-bio-container" id="bibtex">
<h4 class="subtitle" style="margin-top:25px">BibTeX</h4>
<pre><code>@proceedings{naacl2025grounding,
author = {Shi, Freda and Ma, Ziqiao and Mao, Jiayuan and Kordjamshidi, Parisa and Chai, Joyce},
title = {Learning Language through Grounding},
booktitle = {Proceedings of the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts)},
year = {2025},
}</code></pre>
</div>
<div class="main-bio-container" id="bibtex">
<h4 class="subtitle" style="margin-top:25px">Related Tutorial</h4>
<a href="https://spatial-language-tutorial.github.io/">NAACL 2024 Tutorial: Spatial and Temporal Language
Understanding: Representation, Reasoning, and Grounding</a>
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$("#main-pub-card-container").append($("<h5 id='year-" + year.toString() + "' style='padding-top:20px; margin-bottom:10px;'>" + year.toString() + "</h5>"));
}
$("#main-pub-card-container").append(allPublications[pubId]);
}
}
function publicationByTopicInner() {
var a = $("#publication-by-topic")
if (a.hasClass("activated")) {
return;
}
$("#main-pub-container .subtitle a").removeClass("activated");
a.addClass("activated");
$("#main-pub-card-container").html("");
for (var topicId in allTopics) {
var topic = allTopics[topicId].name;
var topicTitle = allTopics[topicId].title;
$("#main-pub-card-container").append($("<h5 id='topic-" + topic + "' style='margin-top:-50px; border-top:70px solid transparent; margin-bottom:10px;'>" + topicTitle + "</h5>"));
for (var pubId = 0; pubId < allPublications.length; pubId++) {
var pub = $(allPublications[pubId]);
if (pub.data("topic").indexOf(topic) != -1) {
$("#main-pub-card-container").append(pub.clone(true));
}
}
}
}
function publicationByTopicSpecificInner(a) {
if ($(a).hasClass("activated")) {
return false;
}
$("#main-pub-container .subtitle-aux a").removeClass("activated");
$(a).addClass("activated");
}
function publicationByTopic() {
publicationByTopicInner();
publicationByTopicSpecificInner($("#main-pub-container .subtitle-aux a:first"));
return true;
}
function publicationByTopicSpecific(a) {
publicationByTopicInner();
publicationByTopicSpecificInner(a);
var hash = a.hash;
$(hash).prop('id', hash.substr(1) + '-noscroll');
window.location.hash = hash;
$(hash + '-noscroll').prop('id', hash.substr(1));
$('html, body').animate({
scrollTop: $(hash).offset().top
}, 1000, function () {
});
return false;
}
$(function () {
getRealSize = function (bgImg) {
var img = new Image();
img.src = bgImg.attr("src");
var width = img.width,
height = img.height;
return {
width: width,
height: height
}
};
getRealWindowSize = function () {
var winWidth = null,
winHeight = null;
if (window.innerWidth) winWidth = window.innerWidth;
else if ((document.body) && (document.body.clientWidth)) winWidth = document.body.clientWidth;
if (window.innerHeight) winHeight = window.innerHeight;
else if ((document.body) && (document.body.clientHeight)) winHeight = document.body.clientHeight;
if (document.documentElement && document.documentElement.clientHeight && document.documentElement.clientWidth) {
winHeight = document.documentElement.clientHeight;
winWidth = document.documentElement.clientWidth
}
return {
width: winWidth,
height: winHeight
}
};
fullBg = function () {
var bgImg = $("#background");
var mainContainer = $("#main");
var firstFire = null;
if (bgImg.length == 0) {
return;
}
function resizeImg() {
var realSize = getRealSize(bgImg);
var imgWidth = realSize.width;
var imgHeight = realSize.height;
if (imgWidth == 0 || imgHeight == 0) {
setTimeout(function () {
resizeImg();
}, 200);
}
console.log(realSize);
var realWinSize = getRealWindowSize();
var winWidth = realWinSize.width;
var winHeight = realWinSize.height;
var widthRatio = winWidth / imgWidth;
var heightRatio = winHeight / imgHeight;
console.log(realWinSize);
if (widthRatio > heightRatio) {
bgImg.width(imgWidth * widthRatio + 'px').height(imgHeight * widthRatio + 'px').css({
'top':
-(imgHeight * widthRatio - winHeight) / 10 * 5 + 'px', 'left': '0'
})
} else {
bgImg.width(imgWidth * heightRatio + 'px').height(imgHeight * heightRatio + 'px').css({
'left':
-(imgWidth * heightRatio - winWidth) / 10 * 3 + 'px', 'top': '0'
})
}
}
resizeImg();
window.onresize = function () {
if (firstFire === null) {
firstFire = setTimeout(function () {
resizeImg();
firstFire = null
}, 100)
}
}
};
targetColor = $("#main-content-container .name").css("color");
animatedLink = function (speed) {
$("#main-content-container .col-link li").hover(function () {
$(this).find('.icon').animate({
color: targetColor,
borderColor: targetColor
}, speed);
$(this).find('.caption').animate({
color: targetColor
})
}, function () {
$(this).find('.icon').animate({
borderColor: '#cccccc',
color: '#cccccc'
}, speed);
$(this).find('.caption').animate({
color: '#cccccc'
})
})
};
animatedLink(400);
allPublications = $("#main-pub-card-container .pub-card");
allTopicsLink = $("#main-pub-container .subtitle-aux a");
allTopics = [];
for (var topicId = 0; topicId < allTopicsLink.length; topicId++) {
allTopics.push({ name: $(allTopicsLink[topicId]).data("topic"), title: $(allTopicsLink[topicId]).html() });
}
$("#publication-by-selected").click();
$("#main-pub-card-container").removeClass("hide");
});
</script>
</body>
</html>