-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathindex.html
345 lines (317 loc) · 15.9 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="description"
content="SIGIR-AP 2024 Tutorial: Retrieval-Enhanced Machine Learning: Synthesis and Opportunities">
<meta name="keywords" content="REML, Information Retrieval, Machine Learning, RAG, SIGIR, SIGIR-AP, SIGIR-AP 2024">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>SIGIR-AP 2024 Tutorial: Retrieval-Enhanced Machine Learning: Synthesis and Opportunities</title>
<link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro"
rel="stylesheet">
<link rel="stylesheet" href="./static/css/bulma.min.css">
<link rel="stylesheet" href="./static/css/bulma-carousel.min.css">
<link rel="stylesheet" href="./static/css/bulma-slider.min.css">
<link rel="stylesheet" href="./static/css/fontawesome.all.min.css">
<link rel="stylesheet" href="./static/css/profile.css">
<link rel="stylesheet"
href="https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css">
<link rel="stylesheet" href="./static/css/index.css">
<link rel="icon" href="./static/images/favicon.svg">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
<script defer src="./static/js/fontawesome.all.min.js"></script>
<script src="./static/js/bulma-carousel.min.js"></script>
<script src="./static/js/bulma-slider.min.js"></script>
<script src="./static/js/index.js"></script>
</head>
<body>
<nav class="navbar" role="navigation" aria-label="main navigation">
<div class="navbar-brand">
<a role="button" class="navbar-burger" aria-label="menu" aria-expanded="false">
<span aria-hidden="true"></span>
<span aria-hidden="true"></span>
<span aria-hidden="true"></span>
</a>
</div>
</nav>
<section class="hero">
<div class="hero-body">
<div class="container is-max-desktop">
<div class="columns is-centered">
<div class="column has-text-centered">
<h1 class="title is-2 publication-title">
<span style="font-size: 80%">SIGIR-AP 2024 Tutorial:</span><br />
Retrieval-Enhanced Machine Learning:<br>Synthesis and Opportunities
</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<table>
<tr>
<!-- <th scope="row">TR-7</th> -->
<!-- <td width="20%" style="text-align: center; padding: 10px"><img width="150px" height="150px" src="static/imgs/profile_fernando.png"></td>
<td width="20%" style="text-align: center; padding: 10px"><img width="150px" height="150px" src="static/imgs/profile_andrew.jpg"></td>
<td width="20%" style="text-align: center; padding: 10px"><img width="150px" height="150px" src="static/imgs/profile_toeun.png"></td>
<td width="20%" style="text-align: center; padding: 10px"><img width="150px" height="150px" src="static/imgs/profile_alireza.jpg"></td>
<td width="20%" style="text-align: center; padding: 10px"><img width="150px" height="150px" src="static/imgs/profile_hamed.jpg"></td> -->
<td class="profile-cell"><img class="profile-img" src="static/imgs/profile_fernando.png" alt="Profile Fernando"></td>
<td class="profile-cell"><img class="profile-img" src="static/imgs/profile_andrew.jpg" alt="Profile Andrew"></td>
<td class="profile-cell"><img class="profile-img" src="static/imgs/profile_toeun.png" alt="Profile Toeun"></td>
<td class="profile-cell"><img class="profile-img" src="static/imgs/profile_alireza.jpg" alt="Profile Alireza"></td>
<td class="profile-cell"><img class="profile-img" src="static/imgs/profile_hamed.jpg" alt="Profile Hamed"></td>
</tr>
<tr>
<!-- <th scope="row">TR-7</th> -->
<td width="20%" style="text-align: center"><a href="https://841.io" style="border-radius: 50%">Fernando Diaz</a><sup>1</sup></td>
<td width="20%" style="text-align: center"><a href="https://mrdrozdov.github.io" style="border-radius: 50%">Andrew Drozdov</a><sup>2</sup></td>
<td width="20%" style="text-align: center"><a href="https://kimdanny.github.io" style="border-radius: 50%">To Eun Kim</a><sup>1</sup></td>
<td width="20%" style="text-align: center"><a href="https://alirezasalemi7.github.io" style="border-radius: 50%">Alireza Salemi</a><sup>3</sup></td>
<td width="20%" style="text-align: center"><a href="https://groups.cs.umass.edu/zamani/" style="border-radius: 50%">Hamed Zamani</a><sup>3</sup></td>
</tr>
</table>
</span>
</div>
<div class="is-size-6 publication-authors">
<span class="author-block"><sup>1</sup>Carnegie Mellon University, </span>
<span class="author-block"><sup>2</sup>Databricks, </span>
<span class="author-block"><sup>3</sup>University of Massachusetts Amherst</span>
</div>
<br />
<div class="is-size-5 publication-authors">
<b>Monday December 9th 14:15 - 17:30 (GMT+9) @ Room 2</b>
</div>
<!-- <div class="is-size-5 publication-authors">
Zoom link available on <a href="https://underline.io/events/395/sessions?eventSessionId=15330&searchGroup=lecture" target="_blank">Underline</a>
</div> -->
</div>
</div>
</div>
</div>
</section>
<section class="section">
<div class="container is-max-desktop">
<!-- Abstract. -->
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">About this tutorial</h2>
<div class="content has-text-justified">
<p>
Retrieval-enhanced machine learning (REML) refers to the use of information retrieval methods to support reasoning and inference in machine learning tasks.
Although relatively recent, these approaches can substantially improve model performance.
This includes improved generalization, knowledge grounding, scalability, freshness, attribution, interpretability and on-device learning.
To date, despite being influenced by work in the information retrieval community,
REML research has predominantly been presented in natural language processing (NLP) conferences.
</p>
<p>
Our tutorial addresses this disconnect by introducing core REML concepts and synthesizing the literature from various domains in machine learning (ML), including but beyond NLP.
What is unique to our approach is that we used consistent notations, to provide researchers with a unified and expandable framework.
This tutorial will be delivered in lecture format based on an existing manuscript: "<a href="https://arxiv.org/abs/2407.12982"><b>Retrieval-Enhanced Machine Learning: Synthesis and Opportunities</b></a>"
</p>
</div>
</div>
</div>
<!--/ Abstract. -->
<!-- Paper video. -->
<!--/ Paper video. -->
</div>
</section>
<section class="section">
<div class="container is-max-desktop">
<div class="columns is-centered">
<div class="column is-full-width">
<h2 class="title is-3">Schedule</h2>
<p>
Our tutorial is scheduled for December 9th from 14:15 to 17:30 (GMT+9). <br>
<!-- <em>Please note that there could be revisions to the presentation slides.</em> -->
<em>Combined Slides: </em>
<a href="static/REML-tutorial-slides.pdf" target='_blank'>[Slides]</a>
</p>
<div class="content has-text-justified">
<style type="text/css">
.tg {border-collapse:collapse;border-spacing:0;}
.tg td{border-color:black;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;
overflow:hidden;padding:10px 5px;word-break:normal;}
.tg th{border-color:black;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;
font-weight:normal;overflow:hidden;padding:10px 5px;word-break:normal;}
.tg .tg-0pky{border-color:inherit;text-align:left;vertical-align:top}
.tg .tg-0lax{text-align:left;vertical-align:top}
</style>
<table class="tg">
<thead>
<tr>
<th class="tg-0pky">Time</th>
<th class="tg-0lax">Section</th>
<th class="tg-0lax">Presenter</th>
<th class="tg-0lax">In <a href="https://arxiv.org/abs/2407.12982">Manuscript</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="tg-0lax">14:15 — 14:35</td>
<td class="tg-0lax">Section 1: Introduction</td>
<td class="tg-0lax">Fernando Diaz</td>
<td class="tg-0lax">Chapter 1 - 2</td>
</tr>
<tr>
<td class="tg-0lax">14:35 — 14:55</td>
<td class="tg-0lax">Section 2: Querying</td>
<td class="tg-0lax">Alireza Salemi</td>
<td class="tg-0lax">Chapter 3</td>
</tr>
<tr>
<td class="tg-0lax">14:55 — 15:05</td>
<td class="tg-0lax">Section 3: Searching</td>
<td class="tg-0lax">Alireza Salemi</td>
<td class="tg-0lax">Chapter 4</td>
</tr>
<tr>
<td class="tg-0lax">15:05 — 15:35</td>
<td class="tg-0lax">Section 4: Presentation & Consumption</td>
<td class="tg-0lax">Andrew Drozdov</td>
<td class="tg-0lax">Chapter 5</td>
</tr>
<tr>
<td class="tg-0lax">15:35 — 16:45</td>
<td class="tg-0lax">Q & A</td>
<td class="tg-0lax">All</td>
<td class="tg-0lax"></td>
</tr>
<tr>
<td class="tg-0lax">15:45 — 16:00</td>
<td class="tg-0lax">Coffee Break</td>
<td class="tg-0lax"></td>
<td class="tg-0lax"></td>
</tr>
<tr>
<td class="tg-0lax">16:00 — 16:30</td>
<td class="tg-0lax">Section 5: Storing</td>
<td class="tg-0lax">To Eun Kim</td>
<td class="tg-0lax">Chapter 6</td>
</tr>
<tr>
<td class="tg-0lax">16:30 — 16:50</td>
<td class="tg-0lax">Section 6: Optimization</td>
<td class="tg-0lax">Hamed Zamani</td>
<td class="tg-0lax">Chapter 7</td>
</tr>
<tr>
<td class="tg-0lax">16:50 — 17:05</td>
<td class="tg-0lax">Section 7: Evaluation</td>
<td class="tg-0lax">Fernando Diaz</td>
<td class="tg-0lax">Chapter 8</td>
</tr>
<tr>
<td class="tg-0lax">17:05 — 17:20</td>
<td class="tg-0lax">Section 8: Future Direction & Conclusion</td>
<td class="tg-0lax">Fernando Diaz</td>
<td class="tg-0lax">Chapter 9 - 10</td>
</tr>
<tr>
<td class="tg-0lax">17:20 — 17:30</td>
<td class="tg-0lax">Q & A</td>
<td class="tg-0lax">All</td>
<td class="tg-0lax"></td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
<!-- Concurrent Work. -->
<!-- <div class="columns is-centered">
<div class="column is-full-width">
<h2 class="title is-3">Reading List</h2>
<p>Coming soon...!</p>
<p>The tutorial extensively covers papers highlighted in <b>bold</b>.</p>
<br>
<h3 class="title is-5">Section 1: Introduction</h3>
<p><b>Sub-title name placeholder</b></pp>
<ul>
<li><a href="https://arxiv.org/abs/2005.11401">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks</a> (Lewis et al. 2022)</li>
<li><a href="https://arxiv.org/abs/2005.11401">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks</a> (Lewis et al. 2022)</li>
<li><a href="https://arxiv.org/abs/2005.11401">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks</a> (Lewis et al. 2022)</li>
<li><a href="https://arxiv.org/abs/2005.11401">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks</a> (Lewis et al. 2022)</li>
</ul>
<br><br>
<h3 class="title is-5">Section 2: Querying</h3>
<p><b>Sub-title name placeholder</b></pp>
<ul>
<li><a href="https://arxiv.org/abs/2005.11401">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks</a> (Lewis et al. 2022)</li>
<li><a href="https://arxiv.org/abs/2005.11401">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks</a> (Lewis et al. 2022)</li>
<li><a href="https://arxiv.org/abs/2005.11401">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks</a> (Lewis et al. 2022)</li>
<li><a href="https://arxiv.org/abs/2005.11401">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks</a> (Lewis et al. 2022)</li>
</ul>
</div>
</div> -->
</section>
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX (Manuscript)</h2>
<pre>
<code>
@misc{kim2024retrievalenhancedmachinelearning,
title={Retrieval-Enhanced Machine Learning: Synthesis and Opportunities},
author={To Eun Kim and Alireza Salemi and Andrew Drozdov and Fernando Diaz and Hamed Zamani},
year={2024},
eprint={2407.12982},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2407.12982},
}
</code>
</pre>
</div>
</section>
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX (Tutorial Proposal)</h2>
<pre>
<code>
@inproceedings{10.1145/3673791.3698439,
author = {Diaz, Fernando and Drozdov, Andrew and Kim, To Eun and Salemi, Alireza and Zamani, Hamed},
title = {Retrieval-Enhanced Machine Learning: Synthesis and Opportunities},
year = {2024},
isbn = {9798400707247},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3673791.3698439},
doi = {10.1145/3673791.3698439},
booktitle = {Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region},
pages = {299–302},
numpages = {4},
keywords = {information retrieval, machine learning},
location = {Tokyo, Japan},
series = {SIGIR-AP 2024}
}
</code>
</pre>
</div>
</section>
<footer class="footer">
<div class="container">
<div class="content has-text-centered">
<a class="icon-link" href="https://github.com/retrieval-enhanced-ml/sigir-ap2024-reml.github.io" class="external-link" disabled>
<i class="fab fa-github"></i>
</a>
</div>
<div class="columns is-centered">
<div class="column is-8">
<div class="content">
<p>
This website is licensed under a <a rel="license"
href="http://creativecommons.org/licenses/by-sa/4.0/">Creative
Commons Attribution-ShareAlike 4.0 International License</a>.
</p>
<p>
This means you are free to borrow the <a
href="https://github.com/nerfies/nerfies.github.io">source code</a> of this website,
we just ask that you link back to this page in the footer.
Please remember to remove the analytics code included in the header of the website which
you do not want on your website.
</p>
</div>
</div>
</div>
</div>
</footer>
</body>
</html>