Dr.-Ing. Hiba Arnaout
I'm a postdoc at the Ubiquitous Knowledge Processing (UKP) Lab (TU Darmstadt), led by Prof. Iryna Gurevych. I obtained my PhD from the Max Planck Institute for Informatics, where I was a member of the Databases and Information Systems Group (advisors: Prof. Gerhard Weikum and Prof. Simon Razniewski). During my PhD, I worked on discovering informative negative statements from encyclopedic and commonsense open-world knowledge bases. During this work I visited The University of Edinburgh where I collaborated with Prof. Jeff Z. Pan. I interned at Bosch Center for Artificial Intelligence (mentor: Dr. Daria Stepanova) where I worked on repairing inconsistent knowledge bases using pretrained language models. I received my Master's of Computer Science from The American University of Beirut (advisor: Prof. Shady Elbassuoni, topic: effective search of RDF Knowledge Bases).
Current topics of interest: AI for mental health, analyzing the impact of research papers, commonsense knowledge, cultural NLP.
Previous topics of interest: searching and curating web-scale knowledge graphs, mining salient negative knowledge.
Education
- PhD in Computer ScienceMax Planck Institute for InformaticsFeb 2018 - Oct 2023Saarbrücken, GermanyAdvisors: Prof. Simon Razniewski, Prof. Gerhard WeikumSWSA Distinguished Dissertation Award
- Master of Computer ScienceAmerican University of BeirutFeb 2014 - Feb 2017Beirut, LebanonAdvisor: Prof. Shady ElbassuoniFull scholarship
- Bachelor of Computer ScienceHaigazian UniversityFeb 2010 - Jun 2013Beirut, Lebanonwith honors
Experience
- PostdocUKP Lab, TU DarmstadtSep 2023 - presentDarmstadt, Germany
- LecturerTU DarmstadtApr 2024 - Jul 2024Darmstadt, Germany
- ResearcherMax Planck Institute for InformaticsFeb 2018 - Oct 2023Saarbrücken, Germany
- Research InternBosch Center for Artificial IntelligenceJun 2021 - Mar 2022Renningen, Germany
- Visiting ResearcherThe University of EdinburghFeb 2020 - Aug 2020Edinburgh, United Kingdom
- Document Control AdministratorAmerican University of BeirutJan 2016 – Dec 2017Beirut, Lebanon
- Research AssistantAmerican University of BeirutFeb 2014 – Jan 2018Beirut, Lebanon
- IT InstructorAmerican University of Beirut & United NationsMar 2017 – Sep 2017Beirut, Lebanon
- Teaching AssistantAmerican University of BeirutFeb 2014 – Dec 2016Beirut, Lebanon
Scholarships and Awards
- Semantic Web Science Association (SWSA) Distinguished Dissertation Award, 2024.
- Reward for invention Knowledge Graph Repair Using Ontologies and LMs, Bosch, 2022.
- Participated in discussion, DFG grant of 312,000 € for compiling negative knowledge at web scale, 2021.
- Audience-choice Best Paper Award at AKBC, 2020.
- Best Student Paper Award Nominee at IC3K'17, 2017.
- Full Graduate Assistantship at the American University of Beirut, 2014.
Student Supervision
- Jan Larionow, Tracking Trends in Mental Health Research: An LLM-based Approach (BSc thesis), April 2025.
- Eugen Owtscharow, Generating Clinically Meaningful Connections in Client Networks (MSc thesis), June 2025.
- Nils Kovacic, LLMs as Culturally-aware Emotional Supporters (BSc thesis), April 2025.
- Serena Baylis, Improving Annotation Tasks over Process-based Therapy Sessions using AI Recommenders (BSc thesis), 2024.
- Malihe Kaffash, Investigating the Implementation of Process-based Theory into Practical Annotations (MSc thesis), 2024.
- Aditya Bikram Biswas (Hiwi), 2021.
- Mang Zhao (Hiwi), 2018.
Publications
(newest to oldest)
Enriching Open-world Knowledge Graphs with Expressive Negative Statements.
Hiba Arnaout
IOS Press 2025
Exploring innovative methods for enhancing knowledge graphs with expressive negative statements, this book will be a valuable resource for those working in knowledge representation, AI, and NLP.
[LINK]
book
In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis
Hiba Arnaout, Noy Sternlicht, Tom Hope, Iryna Gurevych
arXiv 2025
This work introduces time-aware impact summaries capturing evolving citation intents, with strong expert interest and promising evaluation results.
[PAPER] - [WEBPAGE] - [SLIDES]
Completeness, Recall, and Negation in Open-World Knowledge Bases: A Survey.
Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, and Fabian Suchanek
CSUR 2024
In this survey we discuss how knowledge about completeness, recall, and negation in KBs can be expressed, extracted, and inferred.
[PAPER]
journal paper
Wiki-based Communities of Interest: Demographics and Outliers.
Hiba Arnaout, Simon Razniewski, and Jeff Z. Pan
ICWSM 2023
Identified from Wikidata, we construct a datasets about 7.5k communities of interest such as The White House Coronavirus Task Force, covering 345k subjects. Every community comes with interseting findings such as demographic data and exceptional members.
[DEMO] - [PAPER] - [DATA]
dataset paper
UnCommonSense in Action! Informative Negations for Commonsense Knowledge Bases.
Hiba Arnaout, Tuan-Phong Nguyen, Simon Razniewski, and Gerhard Weikum
WSDM 2023
We present a web portal to showcase the Uncommonsense system. Users can browse interesting negative statements about every day concepts such as elephant, pancake, and acne.
[DEMO] - [PAPER]
demo paper
UnCommonSense: Informative Negative Knowledge about Everyday Concepts.
Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
CIKM 2022 Acceptance rate 23%
We introduce UnCommonSense, a method for discovering expressive negative statements about everyday concepts. The method significantly outperforms the state-of-the-art on informativeness and recall.
[WEBPAGE] - [PAPER] - [SLIDES] - [POSTER]
conference paper
Utilizing Language Model Probes for Knowledge Graph Repair.
Hiba Arnaout, Trung-Kien Tran, Daria Stepanova, Mohamed Hassan Gad-Elrab, Simon Razniewski, and Gerhard Weikum
Wikiworkshop at WWW 2022
We present a method to repair incorrect statements in existing knowledge bases by replacing incorrect triples with likely correct ones, thus avoiding information loss. Our method explores the power of LM probes and shows that context retrieval from the knowledge base itself can significantly boost the probing.
[PAPER]
workshop paper
Negative Statements Considered Useful.
Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
JWS 2021
We extend previous methods on negation inference by introducing the order-oriented peer-based inference method, which shows an improvement in informativeness.
[WEBPAGE] - [PAPER]
journal paper
Negative Knowledge for Open-world Wikidata.
Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
WWW Companion 2021
We review Wikidata's attempts to allow negative knowledge and discuss the gains challenges arising from implementing a negation-inference system.
[PAPER]
workshop paper
Neguess: Wikidata-entity Guessing Game with Negative Clues.
Aditya B. Biswas, Hiba Arnaout, and Simon Razniewski
ISWC 2021
We publish an guessing game with unique emphasis on challenging negative clues, e.g., a famous English physicist who has never won a Nobel Prize in Physics?
[DEMO] - [PAPER]
demo paper
Wikinegata: A Knowledge Base with Interesting Negative Statements.
Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
VLDB 2021
A web platform for exploring interesting negative statements about 600k encyclopedic entities.
[DEMO] - [PAPER]
demo paper
Enriching Knowledge Bases with Interesting Negative Statements.
Hiba Arnaout, Simon Razniewski, and Gerhard Weikum
The first publication of my PhD, this work introduces the topic of discovering salient negative statements in open-world knowledge bases and proposes to infer candidates from encyclopedic knowledge bases as well as query logs.
AKBC 2020 Audience-choice best paper award (voted by conference attendees)
[WEBPAGE] - [PAPER] - [SLIDES]
conference paper
Biological Knowledge Graph Construction, Search, and Navigation.
Chandana Tennakoon, Nazar Zaki, Hiba Arnaout, Shady Elbassuoni, Wassim El-Hajj, and Alanoud Al Jaberi
Academic Press 2019
In this book on leveraging biomedical and healthcare data, my contribution is in the writing of chapter 7 on biological knowledge graph construction and search.
[BOOK] - [CHAPTER]
book chapter
Effective Searching of RDF Knowledge Graphs.
Hiba Arnaout and Shady Elbassuoni
JWS 2018 Later presented at ISWC 2018
This publication summarizes my Master thesis. It proposes a framework for searching knowledge graphs using keyword-augmented SPARQL queries and ranking results by both relevance and novelty.
[PAPER] - [SLIDES]
journal paper
Top-k Keyword Search over Wikipedia-based RDF Knowledge Graphs.
Hrag Yoghourdjian, Shady Elbassuoni, Mohamad Jaber, and Hiba Arnaout
KDIR 2017 Best student paper award nominee
This work proposes a novel retrieval model for general keyword queries over the YAGO knowledge graph.
[PAPER]
conference paper
Result Diversity for RDF Search.
Hiba Arnaout and Shady Elbassuoni
KDIR 2016
This paper proposes a method to diversify the results of triple-pattern queries over RDF datasets..
[PAPER]
conference paper
Talks
- In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis, invited talks at TU Dresden and at the 3rd workshop on Bibliometric measures of epistemic change, TU Berlin, 2025. [SLIDES]
- Enriching Open-world Knowledge Graphs with Salient Negative Statements, invited talk at the L3S Research Center, 2023. [SLIDES]
- Negative Statements Considered Useful, invited talk at the Institute for Language, Cognition and Computation (ILCC), The University of Edinburgh, 2022. [SLIDES]
- Completeness, Recall, and Negation in Open-World Knowledge Bases (with Simon Razniewski, Shrestha Ghosh, and Fabian Suchanek), tutorial at KR 2021, ISWC 2021, and WWW 2022. [WEBPAGE]
- On the Limits of Machine Knowledge (with Simon Razniewski, Shrestha Ghosh, and Fabian Suchanek), tutorial at VLDB 2021. [WEBPAGE]
- Enriching Knowledge Bases with Interesting Negative Statements, Forum for presentations of significant Semantic Web-related research at ISWC 2020.
Service
- PC, SPC, and AC: JWS ('22), EMNLP ('21,'22,'23,'24,'25), IJCAI ('21,'22, '23,'24), CIKM ('20,'21, '23), ISWC ('20,'21,'24), ACL ('20,'23), WikiNLP ('25).
- Volunteer: VLDB ('21).
I'm a postdoc at the Ubiquitous Knowledge Processing (UKP) Lab (TU Darmstadt), led by Prof. Iryna Gurevych. I obtained my PhD from the Max Planck Institute for Informatics, where I was a member of the Databases and Information Systems Group (advisors: Prof. Gerhard Weikum and Prof. Simon Razniewski). During my PhD, I worked on discovering informative negative statements from encyclopedic and commonsense open-world knowledge bases. During this work I visited The University of Edinburgh where I collaborated with Prof. Jeff Z. Pan. I interned at Bosch Center for Artificial Intelligence (mentor: Dr. Daria Stepanova) where I worked on repairing inconsistent knowledge bases using pretrained language models. I received my Master's of Computer Science from The American University of Beirut (advisor: Prof. Shady Elbassuoni, topic: effective search of RDF Knowledge Bases).
Current topics of interest: AI for mental health, analyzing the impact of research papers, commonsense knowledge, cultural NLP.
Previous topics of interest: searching and curating web-scale knowledge graphs, mining salient negative knowledge.
Education
- PhD in Computer ScienceMax Planck Institute for InformaticsFeb 2018 - Oct 2023Saarbrücken, GermanyAdvisors: Prof. Simon Razniewski, Prof. Gerhard WeikumSWSA Distinguished Dissertation Award
- Master of Computer ScienceAmerican University of BeirutFeb 2014 - Feb 2017Beirut, LebanonAdvisor: Prof. Shady ElbassuoniFull scholarship
- Bachelor of Computer ScienceHaigazian UniversityFeb 2010 - Jun 2013Beirut, Lebanonwith honors
Experience
- PostdocUKP Lab, TU DarmstadtSep 2023 - presentDarmstadt, Germany
- LecturerTU DarmstadtApr 2024 - Jul 2024Darmstadt, Germany
- ResearcherMax Planck Institute for InformaticsFeb 2018 - Oct 2023Saarbrücken, Germany
- Research InternBosch Center for Artificial IntelligenceJun 2021 - Mar 2022Renningen, Germany
- Visiting ResearcherThe University of EdinburghFeb 2020 - Aug 2020Edinburgh, United Kingdom
- Document Control AdministratorAmerican University of BeirutJan 2016 – Dec 2017Beirut, Lebanon
- Research AssistantAmerican University of BeirutFeb 2014 – Jan 2018Beirut, Lebanon
- IT InstructorAmerican University of Beirut & United NationsMar 2017 – Sep 2017Beirut, Lebanon
- Teaching AssistantAmerican University of BeirutFeb 2014 – Dec 2016Beirut, Lebanon
Scholarships and Awards
- Semantic Web Science Association (SWSA) Distinguished Dissertation Award, 2024.
- Reward for invention Knowledge Graph Repair Using Ontologies and LMs, Bosch, 2022.
- Participated in discussion, DFG grant of 312,000 € for compiling negative knowledge at web scale, 2021.
- Audience-choice Best Paper Award at AKBC, 2020.
- Best Student Paper Award Nominee at IC3K'17, 2017.
- Full Graduate Assistantship at the American University of Beirut, 2014.
Student Supervision
- Jan Larionow, Tracking Trends in Mental Health Research: An LLM-based Approach (BSc thesis), April 2025.
- Eugen Owtscharow, Generating Clinically Meaningful Connections in Client Networks (MSc thesis), June 2025.
- Nils Kovacic, LLMs as Culturally-aware Emotional Supporters (BSc thesis), April 2025.
- Serena Baylis, Improving Annotation Tasks over Process-based Therapy Sessions using AI Recommenders (BSc thesis), 2024.
- Malihe Kaffash, Investigating the Implementation of Process-based Theory into Practical Annotations (MSc thesis), 2024.
- Aditya Bikram Biswas (Hiwi), 2021.
- Mang Zhao (Hiwi), 2018.
Publications
(newest to oldest)Enriching Open-world Knowledge Graphs with Expressive Negative Statements. Hiba Arnaout
IOS Press 2025
Exploring innovative methods for enhancing knowledge graphs with expressive negative statements, this book will be a valuable resource for those working in knowledge representation, AI, and NLP.
[LINK]
book
In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis Hiba Arnaout, Noy Sternlicht, Tom Hope, Iryna Gurevych
arXiv 2025
This work introduces time-aware impact summaries capturing evolving citation intents, with strong expert interest and promising evaluation results.
[PAPER] - [WEBPAGE] - [SLIDES]
Completeness, Recall, and Negation in Open-World Knowledge Bases: A Survey. Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, and Fabian Suchanek
CSUR 2024
In this survey we discuss how knowledge about completeness, recall, and negation in KBs can be expressed, extracted, and inferred.
[PAPER]
journal paper
Wiki-based Communities of Interest: Demographics and Outliers. Hiba Arnaout, Simon Razniewski, and Jeff Z. Pan
ICWSM 2023
Identified from Wikidata, we construct a datasets about 7.5k communities of interest such as The White House Coronavirus Task Force, covering 345k subjects. Every community comes with interseting findings such as demographic data and exceptional members.
[DEMO] - [PAPER] - [DATA]
dataset paper
UnCommonSense in Action! Informative Negations for Commonsense Knowledge Bases. Hiba Arnaout, Tuan-Phong Nguyen, Simon Razniewski, and Gerhard Weikum
WSDM 2023
We present a web portal to showcase the Uncommonsense system. Users can browse interesting negative statements about every day concepts such as elephant, pancake, and acne.
[DEMO] - [PAPER]
demo paper
UnCommonSense: Informative Negative Knowledge about Everyday Concepts. Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
CIKM 2022 Acceptance rate 23%
We introduce UnCommonSense, a method for discovering expressive negative statements about everyday concepts. The method significantly outperforms the state-of-the-art on informativeness and recall.
[WEBPAGE] - [PAPER] - [SLIDES] - [POSTER]
conference paper
Utilizing Language Model Probes for Knowledge Graph Repair. Hiba Arnaout, Trung-Kien Tran, Daria Stepanova, Mohamed Hassan Gad-Elrab, Simon Razniewski, and Gerhard Weikum
Wikiworkshop at WWW 2022
We present a method to repair incorrect statements in existing knowledge bases by replacing incorrect triples with likely correct ones, thus avoiding information loss. Our method explores the power of LM probes and shows that context retrieval from the knowledge base itself can significantly boost the probing.
[PAPER]
workshop paper
Negative Statements Considered Useful. Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
JWS 2021
We extend previous methods on negation inference by introducing the order-oriented peer-based inference method, which shows an improvement in informativeness.
[WEBPAGE] - [PAPER]
journal paper
Negative Knowledge for Open-world Wikidata. Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
WWW Companion 2021
We review Wikidata's attempts to allow negative knowledge and discuss the gains challenges arising from implementing a negation-inference system.
[PAPER]
workshop paper
Neguess: Wikidata-entity Guessing Game with Negative Clues. Aditya B. Biswas, Hiba Arnaout, and Simon Razniewski
ISWC 2021
We publish an guessing game with unique emphasis on challenging negative clues, e.g., a famous English physicist who has never won a Nobel Prize in Physics?
[DEMO] - [PAPER]
demo paper
Wikinegata: A Knowledge Base with Interesting Negative Statements. Hiba Arnaout, Simon Razniewski, Gerhard Weikum, and Jeff Z. Pan
VLDB 2021
A web platform for exploring interesting negative statements about 600k encyclopedic entities.
[DEMO] - [PAPER]
demo paper
Enriching Knowledge Bases with Interesting Negative Statements. Hiba Arnaout, Simon Razniewski, and Gerhard Weikum
The first publication of my PhD, this work introduces the topic of discovering salient negative statements in open-world knowledge bases and proposes to infer candidates from encyclopedic knowledge bases as well as query logs.
AKBC 2020 Audience-choice best paper award (voted by conference attendees) [WEBPAGE] - [PAPER] - [SLIDES]
conference paper
Biological Knowledge Graph Construction, Search, and Navigation. Chandana Tennakoon, Nazar Zaki, Hiba Arnaout, Shady Elbassuoni, Wassim El-Hajj, and Alanoud Al Jaberi
Academic Press 2019
In this book on leveraging biomedical and healthcare data, my contribution is in the writing of chapter 7 on biological knowledge graph construction and search.
[BOOK] - [CHAPTER]
book chapter
Effective Searching of RDF Knowledge Graphs. Hiba Arnaout and Shady Elbassuoni
JWS 2018 Later presented at ISWC 2018
This publication summarizes my Master thesis. It proposes a framework for searching knowledge graphs using keyword-augmented SPARQL queries and ranking results by both relevance and novelty.
[PAPER] - [SLIDES]
journal paper
Top-k Keyword Search over Wikipedia-based RDF Knowledge Graphs. Hrag Yoghourdjian, Shady Elbassuoni, Mohamad Jaber, and Hiba Arnaout
KDIR 2017 Best student paper award nominee
This work proposes a novel retrieval model for general keyword queries over the YAGO knowledge graph.
[PAPER]
conference paper
Result Diversity for RDF Search. Hiba Arnaout and Shady Elbassuoni
KDIR 2016
This paper proposes a method to diversify the results of triple-pattern queries over RDF datasets..
[PAPER]
conference paper
Talks
- In-depth Research Impact Summarization through Fine-Grained Temporal Citation Analysis, invited talks at TU Dresden and at the 3rd workshop on Bibliometric measures of epistemic change, TU Berlin, 2025. [SLIDES]
- Enriching Open-world Knowledge Graphs with Salient Negative Statements, invited talk at the L3S Research Center, 2023. [SLIDES]
- Negative Statements Considered Useful, invited talk at the Institute for Language, Cognition and Computation (ILCC), The University of Edinburgh, 2022. [SLIDES]
- Completeness, Recall, and Negation in Open-World Knowledge Bases (with Simon Razniewski, Shrestha Ghosh, and Fabian Suchanek), tutorial at KR 2021, ISWC 2021, and WWW 2022. [WEBPAGE]
- On the Limits of Machine Knowledge (with Simon Razniewski, Shrestha Ghosh, and Fabian Suchanek), tutorial at VLDB 2021. [WEBPAGE]
- Enriching Knowledge Bases with Interesting Negative Statements, Forum for presentations of significant Semantic Web-related research at ISWC 2020.
Service
- PC, SPC, and AC: JWS ('22), EMNLP ('21,'22,'23,'24,'25), IJCAI ('21,'22, '23,'24), CIKM ('20,'21, '23), ISWC ('20,'21,'24), ACL ('20,'23), WikiNLP ('25).
- Volunteer: VLDB ('21).