3 Search Results for "You, Jia-Huai"

Document
DOI: 10.4230/LIPIcs.CP.2025.17
Scalable Counting of Minimal Trap Spaces and Fixed Points in Boolean Networks

Authors: Mohimenul Kabir, Van-Giang Trinh, Samuel Pastva, and Kuldeep S Meel

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
Boolean Networks (BNs) serve as a fundamental modeling framework for capturing complex dynamical systems across various domains, including systems biology, computational logic, and artificial intelligence. A crucial property of BNs is the presence of trap spaces - subspaces of the state space that, once entered, cannot be exited. Minimal trap spaces, in particular, play a significant role in analyzing the long-term behavior of BNs, making their efficient enumeration and counting essential. The fixed points in BNs are a special case of minimal trap spaces. In this work, we formulate several meaningful counting problems related to minimal trap spaces and fixed points in BNs. These problems provide valuable insights both within BN theory (e.g., in probabilistic reasoning and dynamical analysis) and in broader application areas, including systems biology, abstract argumentation, and logic programming. To address these computational challenges, we propose novel methods based on approximate answer set counting, leveraging techniques from answer set programming. Our approach efficiently approximates the number of minimal trap spaces and the number of fixed points without requiring exhaustive enumeration, making it particularly well-suited for large-scale BNs. Our experimental evaluation on an extensive and diverse set of benchmark instances shows that our methods significantly improve the feasibility of counting minimal trap spaces and fixed points, paving the way for new applications in BN analysis and beyond.
Cite as

Mohimenul Kabir, Van-Giang Trinh, Samuel Pastva, and Kuldeep S Meel. Scalable Counting of Minimal Trap Spaces and Fixed Points in Boolean Networks. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 17:1-17:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{kabir_et_al:LIPIcs.CP.2025.17,
  author =	{Kabir, Mohimenul and Trinh, Van-Giang and Pastva, Samuel and Meel, Kuldeep S},
  title =	{{Scalable Counting of Minimal Trap Spaces and Fixed Points in Boolean Networks}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{17:1--17:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.17},
  URN =		{urn:nbn:de:0030-drops-238780},
  doi =		{10.4230/LIPIcs.CP.2025.17},
  annote =	{Keywords: Computational systems biology, Boolean network, Fixed point, Trap space, Answer set counting, Projected counting, Abstract argumentation, Logic programming}
}
Document
Position
DOI: 10.4230/TGDK.1.1.2
Large Language Models and Knowledge Graphs: Opportunities and Challenges

Authors: Jeff Z. Pan, Simon Razniewski, Jan-Christoph Kalo, Sneha Singhania, Jiaoyan Chen, Stefan Dietze, Hajira Jabeen, Janna Omeliyanenko, Wen Zhang, Matteo Lissandrini, Russa Biswas, Gerard de Melo, Angela Bonifati, Edlira Vakaj, Mauro Dragoni, and Damien Graux

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Large Language Models (LLMs) have taken Knowledge Representation - and the world - by storm. This inflection point marks a shift from explicit knowledge representation to a renewed focus on the hybrid representation of both explicit knowledge and parametric knowledge. In this position paper, we will discuss some of the common debate points within the community on LLMs (parametric knowledge) and Knowledge Graphs (explicit knowledge) and speculate on opportunities and visions that the renewed focus brings, as well as related research topics and challenges.
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Jeff Z. Pan, Simon Razniewski, Jan-Christoph Kalo, Sneha Singhania, Jiaoyan Chen, Stefan Dietze, Hajira Jabeen, Janna Omeliyanenko, Wen Zhang, Matteo Lissandrini, Russa Biswas, Gerard de Melo, Angela Bonifati, Edlira Vakaj, Mauro Dragoni, and Damien Graux. Large Language Models and Knowledge Graphs: Opportunities and Challenges. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 2:1-2:38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{pan_et_al:TGDK.1.1.2,
  author =	{Pan, Jeff Z. and Razniewski, Simon and Kalo, Jan-Christoph and Singhania, Sneha and Chen, Jiaoyan and Dietze, Stefan and Jabeen, Hajira and Omeliyanenko, Janna and Zhang, Wen and Lissandrini, Matteo and Biswas, Russa and de Melo, Gerard and Bonifati, Angela and Vakaj, Edlira and Dragoni, Mauro and Graux, Damien},
  title =	{{Large Language Models and Knowledge Graphs: Opportunities and Challenges}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:38},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.2},
  URN =		{urn:nbn:de:0030-drops-194766},
  doi =		{10.4230/TGDK.1.1.2},
  annote =	{Keywords: Large Language Models, Pre-trained Language Models, Knowledge Graphs, Ontology, Retrieval Augmented Language Models}
}
Document
DOI: 10.4230/LIPIcs.ICLP.2012.235
Reconciling Well-Founded Semantics of DL-Programs and Aggregate Programs

Authors: Jia-Huai You, John Morris, and Yi Bi

Published in: LIPIcs, Volume 17, Technical Communications of the 28th International Conference on Logic Programming (ICLP'12) (2012)

Abstract
Logic programs with aggregates and description logic programs (dl-programs) are two recent extensions to logic programming. In this paper, we study the relationships between these two classes of logic programs, under the well-founded semantics. The main result is that, under a satisfaction-preserving mapping from dl-atoms to aggregates, the well-founded semantics of dl-programs by Eiter et al., coincides with the well-founded semantics of aggregate programs, defined by Pelov et al. as the least fixpoint of a 3-valued immediate consequence operator under the ultimate approximating aggregate. This result enables an alternative definition of the same well-founded semantics for aggregate programs, in terms of the first principle of unfounded sets. Furthermore, the result can be applied, in a uniform manner, to define the well-founded semantics for dl-programs with aggregates, which agrees with the existing semantics when either dl-atoms or aggregates are absent.
Cite as

Jia-Huai You, John Morris, and Yi Bi. Reconciling Well-Founded Semantics of DL-Programs and Aggregate Programs. In Technical Communications of the 28th International Conference on Logic Programming (ICLP'12). Leibniz International Proceedings in Informatics (LIPIcs), Volume 17, pp. 235-246, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{you_et_al:LIPIcs.ICLP.2012.235,
  author =	{You, Jia-Huai and Morris, John and Bi, Yi},
  title =	{{Reconciling Well-Founded Semantics of DL-Programs and Aggregate Programs}},
  booktitle =	{Technical Communications of the 28th International Conference on Logic Programming (ICLP'12)},
  pages =	{235--246},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-43-9},
  ISSN =	{1868-8969},
  year =	{2012},
  volume =	{17},
  editor =	{Dovier, Agostino and Santos Costa, V{\'\i}tor},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICLP.2012.235},
  URN =		{urn:nbn:de:0030-drops-36258},
  doi =		{10.4230/LIPIcs.ICLP.2012.235},
  annote =	{Keywords: Well-founded semantics, description logic programs, aggregate logic programs, three-valued logic.}
}
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