Publications - Current Year

2024

Conference paper

S. Ghosh, S. Razniewski, D. Graux, and G. Weikum

“CardiO: Predicting Cardinality from Online Sources,” in The ACM Web Conference 2024 (WWW 2024), Singapore.

BibTeX

@inproceedings{Ghosh_WWW2024,
TITLE = {{CardiO}: Predicting Cardinality from Online Sources},
AUTHOR = {Ghosh, Shrestha and Razniewski, Simon and Graux, Damien and Weikum, Gerhard},
LANGUAGE = {eng},
PUBLISHER = {ACM},
YEAR = {2024},
PUBLREMARK = {Accepted},
BOOKTITLE = {The ACM Web Conference 2024 (WWW 2024)},
ADDRESS = {Singapore},
}

Endnote

%0 Conference Proceedings
%A Ghosh, Shrestha
%A Razniewski, Simon
%A Graux, Damien
%A Weikum, Gerhard
%+ Databases and Information Systems, MPI for Informatics, Max Planck Society
Databases and Information Systems, MPI for Informatics, Max Planck Society
External Organizations
Databases and Information Systems, MPI for Informatics, Max Planck Society
%T CardiO: Predicting Cardinality from Online Sources : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000F-13B6-E
%D 2024
%B ACM Web Conference
%Z date of event: 2024-05-13 - 2024-05-17
%C Singapore
%B The ACM Web Conference 2024
%I ACM

Conference paper

Z. Jia, P. Christmann, and G. Weikum

“Faithful Temporal Question Answering over Heterogeneous Sources,” in The ACM Web Conference 2024 (WWW 2024), Singapore.

mehr

BibTeX

@inproceedings{Jia_WWW2024,
TITLE = {Faithful Temporal Question Answering over Heterogeneous Sources},
AUTHOR = {Jia, Zhen and Christmann, Philipp and Weikum, Gerhard},
LANGUAGE = {eng},
PUBLISHER = {ACM},
YEAR = {2024},
PUBLREMARK = {Accepted},
BOOKTITLE = {The ACM Web Conference 2024 (WWW 2024)},
ADDRESS = {Singapore},
}

Endnote

%0 Conference Proceedings
%A Jia, Zhen
%A Christmann, Philipp
%A Weikum, Gerhard
%+ External Organizations
Databases and Information Systems, MPI for Informatics, Max Planck Society
Databases and Information Systems, MPI for Informatics, Max Planck Society
%T Faithful Temporal Question Answering over Heterogeneous Sources : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000E-7D1D-7
%D 2024
%B ACM Web Conference
%Z date of event: 2024-05-13 - 2024-05-17
%C Singapore
%B The ACM Web Conference 2024
%I ACM

Paper

T.-P. Nguyen, S. Razniewski, and G. Weikum

“Multi-Cultural Commonsense Knowledge Distillation,” 2024. [Online]. Available: https://arxiv.org/abs/2402.10689.

mehr

Abstract

Despite recent progress, large language models (LLMs) still face the
challenge of appropriately reacting to the intricacies of social and cultural
conventions. This paper presents MANGO, a methodology for distilling
high-accuracy, high-recall assertions of cultural knowledge. We judiciously and
iteratively prompt LLMs for this purpose from two entry points, concepts and
cultures. Outputs are consolidated via clustering and generative summarization.
Running the MANGO method with GPT-3.5 as underlying LLM yields 167K
high-accuracy assertions for 30K concepts and 11K cultures, surpassing prior
resources by a large margin. For extrinsic evaluation, we explore augmenting
dialogue systems with cultural knowledge assertions. We find that adding
knowledge from MANGO improves the overall quality, specificity, and cultural
sensitivity of dialogue responses, as judged by human annotators. Data and code
are available for download.

BibTeX

@online{Nguyen2402.10689,
TITLE = {Multi-Cultural Commonsense Knowledge Distillation},
AUTHOR = {Nguyen, Tuan-Phong and Razniewski, Simon and Weikum, Gerhard},
LANGUAGE = {eng},
URL = {https://arxiv.org/abs/2402.10689},
EPRINT = {2402.10689},
EPRINTTYPE = {arXiv},
YEAR = {2024},
ABSTRACT = {Despite recent progress, large language models (LLMs) still face the<br>challenge of appropriately reacting to the intricacies of social and cultural<br>conventions. This paper presents MANGO, a methodology for distilling<br>high-accuracy, high-recall assertions of cultural knowledge. We judiciously and<br>iteratively prompt LLMs for this purpose from two entry points, concepts and<br>cultures. Outputs are consolidated via clustering and generative summarization.<br>Running the MANGO method with GPT-3.5 as underlying LLM yields 167K<br>high-accuracy assertions for 30K concepts and 11K cultures, surpassing prior<br>resources by a large margin. For extrinsic evaluation, we explore augmenting<br>dialogue systems with cultural knowledge assertions. We find that adding<br>knowledge from MANGO improves the overall quality, specificity, and cultural<br>sensitivity of dialogue responses, as judged by human annotators. Data and code<br>are available for download.<br>},
}

Endnote

%0 Report
%A Nguyen, Tuan-Phong
%A Razniewski, Simon
%A Weikum, Gerhard
%+ Databases and Information Systems, MPI for Informatics, Max Planck Society
External Organizations
Databases and Information Systems, MPI for Informatics, Max Planck Society
%T Multi-Cultural Commonsense Knowledge Distillation : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000E-7348-0
%U https://arxiv.org/abs/2402.10689
%D 2024
%X   Despite recent progress, large language models (LLMs) still face the<br>challenge of appropriately reacting to the intricacies of social and cultural<br>conventions. This paper presents MANGO, a methodology for distilling<br>high-accuracy, high-recall assertions of cultural knowledge. We judiciously and<br>iteratively prompt LLMs for this purpose from two entry points, concepts and<br>cultures. Outputs are consolidated via clustering and generative summarization.<br>Running the MANGO method with GPT-3.5 as underlying LLM yields 167K<br>high-accuracy assertions for 30K concepts and 11K cultures, surpassing prior<br>resources by a large margin. For extrinsic evaluation, we explore augmenting<br>dialogue systems with cultural knowledge assertions. We find that adding<br>knowledge from MANGO improves the overall quality, specificity, and cultural<br>sensitivity of dialogue responses, as judged by human annotators. Data and code<br>are available for download.<br>
%K Computer Science, Computation and Language, cs.CL

Article

S. Razniewski, H. Arnaout, S. Ghosh, and F. Suchanek

“Completeness, Recall, and Negation in Open-world Knowledge Bases: A Survey,” ACM Computing Surveys, vol. 56, no. 6, 2024.

mehr

BibTeX

@article{Razniewski24,
TITLE = {Completeness, Recall, and Negation in Open-world Knowledge Bases: {A} Survey},
AUTHOR = {Razniewski, Simon and Arnaout, Hiba and Ghosh, Shrestha and Suchanek, Fabian},
LANGUAGE = {eng},
ISSN = {0360-0300; 1557-7341},
DOI = {10.1145/3639563},
PUBLISHER = {ACM},
ADDRESS = {New York, NY},
YEAR = {2024},
DATE = {2024},
JOURNAL = {ACM Computing Surveys},
VOLUME = {56},
NUMBER = {6},
PAGES = {1--42},
EID = {150},
}

Endnote

%0 Journal Article
%A Razniewski, Simon
%A Arnaout, Hiba
%A Ghosh, Shrestha
%A Suchanek, Fabian
%+ External Organizations
External Organizations
Databases and Information Systems, MPI for Informatics, Max Planck Society
External Organizations
%T Completeness, Recall, and Negation in Open-world Knowledge Bases: A Survey : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000E-76FD-1
%R 10.1145/3639563
%D 2024
%J ACM Computing Surveys
%O ACM Comput. Surv. Computing surveys CSUR
%V 56
%N 6
%& 1
%P 1 - 42
%Z sequence number: 150
%I ACM
%C New York, NY
%@ false

Conference paper

G. H. Torbati, A. Tigunova, and G. Weikum

“SIRUP: Search-based Book Recommendation Playground,” in WSDM ’24, 17th ACM International Conference on Web Search and Data Mining, Merida, Mexico, 2024.

mehr

BibTeX

@inproceedings{TorbatiWSDM24,
TITLE = {{SIRUP}: {S}earch-based Book Recommendation Playground},
AUTHOR = {Torbati, Ghazaleh Haratinezhad and Tigunova, Anna and Weikum, Gerhard},
LANGUAGE = {eng},
ISBN = {979-8-4007-0371-3},
DOI = {10.1145/3616855.3635692},
PUBLISHER = {ACM},
YEAR = {2024},
DATE = {2024},
BOOKTITLE = {WSDM '24, 17th ACM International Conference on Web Search and Data Mining},
EDITOR = {Ang{\'e}lica Caudillo Mata, Luz and Lattanzi, Silvio and Mu{\~n}oz Medina, Andr{\'e}s and Akoglu, Leman and Gionis, Aristides and Vassilvitskii, Sergei},
PAGES = {1062--1065},
ADDRESS = {Merida, Mexico},
}

Endnote

%0 Conference Proceedings
%A Torbati, Ghazaleh Haratinezhad
%A Tigunova, Anna
%A Weikum, Gerhard
%+ Databases and Information Systems, MPI for Informatics, Max Planck Society
Databases and Information Systems, MPI for Informatics, Max Planck Society
Databases and Information Systems, MPI for Informatics, Max Planck Society
%T SIRUP: Search-based Book Recommendation Playground : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000E-A663-7
%R 10.1145/3616855.3635692
%D 2024
%B 17th ACM International Conference on Web Search and Data Mining
%Z date of event: 2024-03-04 - 2024-03-08
%C Merida, Mexico
%B WSDM '24
%E Ang&#233;lica Caudillo Mata, Luz; Lattanzi, Silvio; Mu&#241;oz Medina, Andr&#233;s; Akoglu, Leman; Gionis, Aristides; Vassilvitskii, Sergei
%P 1062 - 1065
%I ACM
%@ 979-8-4007-0371-3

Conference paper

H. D. Tran, A. Yates, and G. Weikum

“Conversational Search with Tail Entities,” in Advances in Information Retrieval (ECIR 2024), Glasgow, UK, 2024.

mehr

BibTeX

@inproceedings{Tran_ECIR24,
TITLE = {Conversational Search with Tail Entities},
AUTHOR = {Tran, Hai Dang and Yates, Andrew and Weikum, Gerhard},
LANGUAGE = {eng},
ISBN = {978-3-031-56059-0},
DOI = {10.1007/978-3-031-56060-6_20},
PUBLISHER = {Springer},
YEAR = {2024},
DATE = {2024},
BOOKTITLE = {Advances in Information Retrieval (ECIR 2024)},
EDITOR = {Goharian, Nazli and Tonellotto, Nicola and He, Yulan and Lipani, Aldo and McDonald, Graham and Macdonald, Craig and Ounis, Iadh},
PAGES = {303--317},
SERIES = {Lecture Notes in Computer Science},
VOLUME = {14609},
ADDRESS = {Glasgow, UK},
}

Endnote

%0 Conference Proceedings
%A Tran, Hai Dang
%A Yates, Andrew
%A Weikum, Gerhard
%+ Databases and Information Systems, MPI for Informatics, Max Planck Society
Databases and Information Systems, MPI for Informatics, Max Planck Society
Databases and Information Systems, MPI for Informatics, Max Planck Society
%T Conversational Search with Tail Entities : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000F-042C-C
%R 10.1007/978-3-031-56060-6_20
%D 2024
%B 46th European Conference on Information Retrieval
%Z date of event: 2024-03-24 - 2024-03-28
%C Glasgow, UK
%B Advances in Information Retrieval
%E Goharian, Nazli; Tonellotto, Nicola; He, Yulan; Lipani, Aldo; McDonald, Graham; Macdonald, Craig; Ounis, Iadh
%P 303 - 317
%I Springer
%@ 978-3-031-56059-0
%B Lecture Notes in Computer Science
%N 14609