[Meetings] [CFP] First International Workshop on LLMs and KRR for Trustworthy AI (LMKR-TrustAI 2025)
Yang Song via clean-list <[email protected]> Fri, 18 Jul 2025 05:22:47 +0000
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First International Workshop on LLMs and KRR for Trustworthy AI (LMKR-Trust=
AI 2025)
Held in conjunction with KR 2025<https://eur01.safelinks.protection.outlook=
.com/?url=3Dhttps%3A%2F%2Fkr.org%2FKR2025%2F&data=3D05%7C02%7Cclean-list%40=
science.ru.nl%7Cd0932611f64f45da910d08ddc5bb34f3%7C084578d9400d4a5aa7c7e76c=
a47af400%7C1%7C0%7C638884130033738367%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hc=
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D&reserved=3D0>
Half day, 11-13 November 2025 (TBD)
Paper submission: August 4, 2025
Workshop web site: https://eur01.safelinks.protection.outlook.com/?url=3Dht=
tps%3A%2F%2Fsites.google.com%2Fview%2Flmkr-trustai-2025%2Fhome&data=3D05%7C=
02%7Cclean-list%40science.ru.nl%7Cd0932611f64f45da910d08ddc5bb34f3%7C084578=
d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638884130033760050%7CUnknown%7CTWFpbGZ=
sb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTW=
FpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=3DSRj3C10Mzzgfe%2ByQ%2BdoZDlDMyfP=
AhJvXX2s8B27vhQo%3D&reserved=3D0
Call for Papers
Overview
The emergence of large language models (LLMs) has brought significant oppor=
tunities for developing scalable and generalisable AI applications more eas=
ily. Compared to knowledge representation and reasoning (KRR) methods, LLMs=
demonstrate remarkable capability in encoding linguistic knowledge, enabli=
ng them to generate human-like text and generalise across diverse tasks wit=
h minimal domain-specific training. However, LLMs=92 reliance on statistica=
l patterns rather than explicit reasoning mechanisms raises concerns about =
factual consistency, logical coherence, vulnerability to hallucinations, bi=
as and misalignment with human values. This workshop focuses on an emerging=
research paradigm: the integration of LLMs with KRR techniques to enhance =
transparency, verifiability and robustness in AI systems. We explore approa=
ches that incorporate structured knowledge (ontologies, knowledge graphs, s=
ymbolic logic, etc.), neuro-symbolic methods, formal reasoning frameworks a=
nd explainability techniques to improve the trustworthiness of LLM-driven d=
ecision-making.
The workshop will feature invited talks from leading experts, research pape=
r presentations, and interactive discussions on bridging probabilistic lear=
ning with symbolic reasoning for trustworthy AI. By bringing together resea=
rchers from KRR and deep learning, this workshop aims to foster new collabo=
rations and technical insights to develop AI systems that are both powerful=
and trustworthy.
Topics of interest include but are not limited to:
*
Knowledge-grounded language models
*
Hybrid neuro-symbolic architectures
*
Reasoning-aware prompt engineering
*
Logical consistency checks in LLM outputs
*
Uncertainty and automated verification
*
Causality and reasoning
*
Explainability and controllability
*
Commonsense reasoning integrating LLMs and KRR
*
Reinforcement learning for ensuring safety and trustworthiness
*
Alignment and preference-guided LLMs
*
Multi-agent AI frameworks
*
Benchmarks, datasets and quantitative evaluation metrics
*
Evaluation and user studies in real-world applications
Organising Committee
* Maurice Pagnucco, UNSW, Australia
* Yang Song, UNSW, Australia
Program Committee
*
Professor Tony Cohn, University of Leeds, UK
*
Dr Mingming Gong, University of Melbourne, Australia
*
Professor Gerhard Lakemeyer, RWTH Aachen, Germany
*
Professor Fangzhen Lin, HKUST, China
*
Professor Tim Miller, University of Queensland, Australia
*
Dr Nina Narodytska, VMware Research, USA
*
Associate Professor Abhaya Nayak, Macquarie University, Australia
*
Professor Ken Satoh, National Institute of Informatics, Japan
*
Professor Michael Thielscher, University of New South Wales, Australia
*
Professor Guy Van den Broeck, UCLA, USA
Important Dates
Paper submission: August 4, 2025
Paper notification: August 25, 2025
Workshop date and time: Half-day during November 11-13, 2025 (TBD)
Submissions
Contributions may be regular papers (up to 9 pages) or short/position paper=
s (up to 5 pages), including everything. Submissions should follow the KR 2=
025 formatting guidelines and be submitted through the submission page. Eac=
h submission will be reviewed by at least two program committee members. We=
also welcome submissions that have recently been accepted in top AI confer=
ences. At least one author of each accepted paper will be required to atten=
d the workshop to present the contribution.
Submission link: https://eur01.safelinks.protection.outlook.com/?url=3Dhttp=
s%3A%2F%2Fopenreview.net%2Fgroup%3Fid%3Dkr.org%2FKR%2F2025%2FWorkshop%2FLMK=
R-TrustAI&data=3D05%7C02%7Cclean-list%40science.ru.nl%7Cd0932611f64f45da910=
d08ddc5bb34f3%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C6388841300337731=
21%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAi=
OiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=3DdpADIsw0v=
VBk9aY7BUhgh0VEJHx74gPpbIcR1Umnb2s%3D&reserved=3D0
Best regards,
Maurice Pagnucco, Yang Song
Organisers, KR 2025 Workshop on LLMs and KRR for Trustworthy AI
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<span style=3D"background-color: rgb(255, 255, 255);"><b>First Internationa=
l Workshop on LLMs and KRR for Trustworthy AI (LMKR-TrustAI 2025)</b></span=
></div>
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Held in conjunction with <a title=3D"https://kr.org/KR2025/" href=3D"https:=
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KR 2025</a></div>
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Half day, 11-13 November 2025 (TBD) </div>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin: 0=
px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
Paper submission: August 4, 2025</div>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin: 0=
px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
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uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
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Workshop web site: <a href=3D"https://eur01.safelinks.protection.outlook.co=
m/?url=3Dhttps%3A%2F%2Fsites.google.com%2Fview%2Flmkr-trustai-2025%2Fhome&a=
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://sites.google.com/view/lmkr-trustai-2025/home">
https://sites.google.com/view/lmkr-trustai-2025/home</a> </div>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin: 0=
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uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
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<b><br>
</b></div>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin: 0=
px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
<b>Call for Papers<br>
</b><br>
<b>Overview</b></div>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin: 0=
px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
The emergence of large language models (LLMs) has brought significant oppor=
tunities for developing scalable and generalisable AI applications more eas=
ily. Compared to knowledge representation and reasoning (KRR) methods, LLMs=
demonstrate remarkable capability
in encoding linguistic knowledge, enabling them to generate human-like tex=
t and generalise across diverse tasks with minimal domain-specific training=
. However, LLMs=92 reliance on statistical patterns rather than explicit re=
asoning mechanisms raises concerns
about factual consistency, logical coherence, vulnerability to hallucinati=
ons, bias and misalignment with human values. This workshop focuses on an e=
merging research paradigm: the integration of LLMs with KRR techniques to e=
nhance transparency, verifiability
and robustness in AI systems. We explore approaches that incorporate struc=
tured knowledge (ontologies, knowledge graphs, symbolic logic, etc.), neuro=
-symbolic methods, formal reasoning frameworks and explainability technique=
s to improve the trustworthiness
of LLM-driven decision-making.</div>
<div style=3D"font-family: "Segoe UI", "Segoe UI Web (West E=
uropean)", "Helvetica Neue", sans-serif; font-size: 15px; co=
lor: rgb(36, 36, 36);" class=3D"elementToProof">
<br>
</div>
<div style=3D"font-family: "Segoe UI", "Segoe UI Web (West E=
uropean)", "Helvetica Neue", sans-serif; font-size: 15px; co=
lor: rgb(36, 36, 36);" class=3D"elementToProof">
The workshop will feature invited talks from leading experts, research pape=
r presentations, and interactive discussions on bridging probabilistic lear=
ning with symbolic reasoning for trustworthy AI. By bringing together resea=
rchers from KRR and deep learning,
this workshop aims to foster new collaborations and technical insights to =
develop AI systems that are both powerful and trustworthy.</div>
<div style=3D"direction: ltr; text-align: left; margin-right: 0px; margin-l=
eft: 0px; font-family: "Segoe UI", "Segoe UI Web (West Europ=
ean)", "Helvetica Neue", sans-serif; font-size: 15px; color:=
rgb(36, 36, 36);" class=3D"elementToProof">
<br>
Topics of interest include but are not limited to:</div>
<ul style=3D"direction: ltr; text-align: left; list-style-type: disc; flex-=
direction: column; display: flex;" data-editing-info=3D"{"orderedStyle=
Type":1,"unorderedStyleType":1}">
<li style=3D"font-family: "Segoe UI", "Segoe UI Web (West Eu=
ropean)", "Helvetica Neue", sans-serif; font-size: 15px; col=
or: rgb(36, 36, 36); direction: ltr; align-self: start; text-indent: 0px;">
<div role=3D"presentation" class=3D"elementToProof">Knowledge-grounded lang=
uage models</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Hybrid neuro-symbolic a=
rchitectures</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Reasoning-aware prompt =
engineering</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Logical consistency che=
cks in LLM outputs</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Uncertainty and automat=
ed verification</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Causality and reasoning=
</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Explainability and cont=
rollability</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Commonsense reasoning i=
ntegrating LLMs and KRR</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Reinforcement learning =
for ensuring safety and trustworthiness</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Alignment and preferenc=
e-guided LLMs</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Multi-agent AI framewor=
ks</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Benchmarks, datasets an=
d quantitative evaluation metrics</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Evaluation and user stu=
dies in real-world applications</div>
</li></ul>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin: 0=
px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
<b>Organising Committee</b></div>
<ul style=3D"direction: ltr; text-align: left; list-style-type: disc; flex-=
direction: column; display: flex;" data-editing-info=3D"{"orderedStyle=
Type":1,"unorderedStyleType":1}">
<li style=3D"font-family: "Segoe UI", "Segoe UI Web (West Eu=
ropean)", "Helvetica Neue", sans-serif; font-size: 15px; col=
or: rgb(36, 36, 36); direction: ltr; align-self: start;">
Maurice Pagnucco, UNSW, Australia<br>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36); direction: ltr; align-self: start; margin: 0px;">
Yang Song, UNSW, Australia</li></ul>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin-ri=
ght: 0px; margin-left: 0px; font-family: "Segoe UI", "Segoe =
UI Web (West European)", "Helvetica Neue", sans-serif; font-=
size: 15px; color: rgb(36, 36, 36);" class=3D"elementToProof">
<b>Program Committee</b></div>
<ul style=3D"direction: ltr; text-align: left; list-style-type: disc; flex-=
direction: column; display: flex;" data-editing-info=3D"{"orderedStyle=
Type":1,"unorderedStyleType":1}">
<li style=3D"font-family: "Segoe UI", "Segoe UI Web (West Eu=
ropean)", "Helvetica Neue", sans-serif; font-size: 15px; col=
or: rgb(36, 36, 36); direction: ltr; align-self: start; text-indent: 0px;">
<div role=3D"presentation" class=3D"elementToProof">Professor Tony Cohn, Un=
iversity of Leeds, UK</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Dr Mingming Gong, Unive=
rsity of Melbourne, Australia</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Professor Gerhard Lakem=
eyer, RWTH Aachen, Germany</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Professor Fangzhen Lin,=
HKUST, China</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Professor Tim Miller, U=
niversity of Queensland, Australia</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Dr Nina Narodytska, VMw=
are Research, USA</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Associate Professor Abh=
aya Nayak, Macquarie University, Australia</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Professor Ken Satoh, Na=
tional Institute of Informatics, Japan</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Professor Michael Thiel=
scher, University of New South Wales, Australia</div>
</li><li style=3D"font-family: "Segoe UI", "Segoe UI Web (We=
st European)", "Helvetica Neue", sans-serif; font-size: 15px=
; color: rgb(36, 36, 36);">
<div role=3D"presentation" class=3D"elementToProof">Professor Guy Van den B=
roeck, UCLA, USA</div>
</li></ul>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin-ri=
ght: 0px; margin-left: 0px; font-family: "Segoe UI", "Segoe =
UI Web (West European)", "Helvetica Neue", sans-serif; font-=
size: 15px; color: rgb(36, 36, 36);" class=3D"elementToProof">
<b>Important Dates</b><br>
<br>
</div>
<div style=3D"direction: ltr; text-align: left; margin-right: 0px; margin-l=
eft: 0px; font-family: "Segoe UI", "Segoe UI Web (West Europ=
ean)", "Helvetica Neue", sans-serif; font-size: 15px; color:=
rgb(36, 36, 36);" class=3D"elementToProof">
Paper submission: August 4, 2025</div>
<div style=3D"font-family: "Segoe UI", "Segoe UI Web (West E=
uropean)", "Helvetica Neue", sans-serif; font-size: 15px; co=
lor: rgb(36, 36, 36);" class=3D"elementToProof">
Paper notification: August 25, 2025</div>
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uropean)", "Helvetica Neue", sans-serif; font-size: 15px; co=
lor: rgb(36, 36, 36);" class=3D"elementToProof">
Workshop date and time: Half-day during November 11-13, 2025 (TBD)</div>
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px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
<br>
</div>
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ght: 0px; margin-left: 0px; font-family: "Segoe UI", "Segoe =
UI Web (West European)", "Helvetica Neue", sans-serif; font-=
size: 15px; color: rgb(36, 36, 36);" class=3D"elementToProof">
<b>Submissions</b></div>
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px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
Contributions may be regular papers (up to 9 pages) or short/position paper=
s (up to 5 pages), including everything. Submissions should follow the KR 2=
025 formatting guidelines and be submitted through the submission page. Eac=
h submission will be reviewed by
at least two program committee members. We also welcome submissions that h=
ave recently been accepted in top AI conferences. At least one author of ea=
ch accepted paper will be required to attend the workshop to present the co=
ntribution.<br>
Submission link: <a href=3D"https://eur01.safelinks.protection.outlook.com/=
?url=3Dhttps%3A%2F%2Fopenreview.net%2Fgroup%3Fid%3Dkr.org%2FKR%2F2025%2FWor=
kshop%2FLMKR-TrustAI&data=3D05%7C02%7Cclean-list%40science.ru.nl%7Cd093=
2611f64f45da910d08ddc5bb34f3%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C6=
38884130033829430%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwL=
jAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&am=
p;sdata=3D7hQwZiGOnH5JLCt6uAEhQU7Hk3LAu%2BF5beFbLQgJ%2Fcg%3D&reserved=
=3D0" originalSrc=3D"https://openreview.net/group?id=3Dkr.org/KR/2025/Works=
hop/LMKR-TrustAI">
https://openreview.net/group?id=3Dkr.org/KR/2025/Workshop/LMKR-TrustAI</a>&=
nbsp;</div>
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px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
<br>
</div>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin: 0=
px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
Best regards,</div>
<div style=3D"direction: ltr; text-align: left; text-indent: 0px; margin: 0=
px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
Maurice Pagnucco, Yang Song</div>
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px; font-family: "Segoe UI", "Segoe UI Web (West European)&q=
uot;, "Helvetica Neue", sans-serif; font-size: 15px; color: rgb(3=
6, 36, 36);" class=3D"elementToProof">
Organisers, KR 2025 Workshop on LLMs and KRR for Trustworthy AI </div>
</div>
</div>
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uropean)", "Helvetica Neue", sans-serif; font-size: 11pt; co=
lor: rgb(0, 0, 0);" class=3D"elementToProof">
<br>
</div>
<div style=3D"font-family: "Segoe UI", "Segoe UI Web (West E=
uropean)", "Helvetica Neue", sans-serif; font-size: 11pt; co=
lor: rgb(0, 0, 0);" class=3D"elementToProof">
<br>
</div>
<br>
<p><em><strong>Confidential communication</strong> - This email and any fil=
es transmitted with it are confidential and are intended solely for the add=
ressee. If you are not the intended recipient, please be advised that you h=
ave received this email in error
and that any use, dissemination, forwarding, printing, or copying of this =
email and any file attachments is strictly prohibited. If you have received=
this email in error, please notify me immediately by return email and dest=
roy this email.</em></p>
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