26 Search Results for "Li, Chu-Min"

Document
PACE Solver Description
DOI: 10.4230/LIPIcs.IPEC.2025.40
PACE Solver Description: Weighting-Based Local Search Heuristic for the Hitting Set Problem

Authors: Canhui Luo, Qingyun Zhang, Zhouxing Su, and Zhipeng Lü

Published in: LIPIcs, Volume 358, 20th International Symposium on Parameterized and Exact Computation (IPEC 2025)

Abstract
We present a unified heuristic solver for the PACE 2025 challenge, addressing both the dominating set and hitting set problems by reducing them to the unicost set covering problem. Our solver applies standard reduction rules, a multi-round frequency-based greedy initializer, and a local search guided by adaptive element weights. Additional techniques, such as component-level exact solving and swap restriction, further enhance performance. In the final official evaluation, our proposed solver achieved second place in the heuristic track for the dominating set problem of the PACE 2025 challenge, while securing first place in the heuristic track for the hitting set problem.
Cite as

Canhui Luo, Qingyun Zhang, Zhouxing Su, and Zhipeng Lü. PACE Solver Description: Weighting-Based Local Search Heuristic for the Hitting Set Problem. In 20th International Symposium on Parameterized and Exact Computation (IPEC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 358, pp. 40:1-40:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{luo_et_al:LIPIcs.IPEC.2025.40,
  author =	{Luo, Canhui and Zhang, Qingyun and Su, Zhouxing and L\"{u}, Zhipeng},
  title =	{{PACE Solver Description: Weighting-Based Local Search Heuristic for the Hitting Set Problem}},
  booktitle =	{20th International Symposium on Parameterized and Exact Computation (IPEC 2025)},
  pages =	{40:1--40:4},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-407-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{358},
  editor =	{Agrawal, Akanksha and van Leeuwen, Erik Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.IPEC.2025.40},
  URN =		{urn:nbn:de:0030-drops-251728},
  doi =		{10.4230/LIPIcs.IPEC.2025.40},
  annote =	{Keywords: PACE 2025, Dominating Set, Hitting Set, Heuristic Optimization, Weighted Local Search}
}
Document
Research
DOI: 10.4230/TGDK.3.3.4
Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web

Authors: Florian Ruosch, Cristina Sarasua, and Abraham Bernstein

Published in: TGDK, Volume 3, Issue 3 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 3

Abstract
In Argument Mining, predicting argumentative relations between texts (or spans) remains one of the most challenging aspects, even more so in the cross-document setting. This paper makes three key contributions to advance research in this domain. We first extend an existing dataset, the Sci-Arg corpus, by annotating it with explicit inter-document argumentative relations, thereby allowing arguments to be distributed over several documents forming an Argument Web; these new annotations are published using Semantic Web technologies (RDF, OWL). Second, we explore and evaluate three automated approaches for predicting these inter-document argumentative relations, establishing critical baselines on the new dataset. We find that a simple classifier based on discourse indicators with access to context outperforms neural methods. Third, we conduct a comparative analysis of these approaches for both intra- and inter-document settings, identifying statistically significant differences in results that indicate the necessity of distinguishing between these two scenarios. Our findings highlight significant challenges in this complex domain and open crucial avenues for future research on the Argument Web of Science, particularly for those interested in leveraging Semantic Web technologies and knowledge graphs to understand scholarly discourse. With this, we provide the first stepping stones in the form of a benchmark dataset, three baseline methods, and an initial analysis for a systematic exploration of this field relevant to the Web of Data and Science.
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Florian Ruosch, Cristina Sarasua, and Abraham Bernstein. Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 4:1-4:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{ruosch_et_al:TGDK.3.3.4,
  author =	{Ruosch, Florian and Sarasua, Cristina and Bernstein, Abraham},
  title =	{{Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:33},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.4},
  URN =		{urn:nbn:de:0030-drops-252159},
  doi =		{10.4230/TGDK.3.3.4},
  annote =	{Keywords: Argument Mining, Large Language Models, Knowledge Graphs, Link Prediction}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2025.25
On the Interplay of Cube Learning and Dependency Schemes in {QCDCL} Proof Systems

Authors: Abhimanyu Choudhury and Meena Mahajan

Published in: LIPIcs, Volume 360, 45th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2025)

Abstract
Quantified Conflict Driven Clause Leaning (QCDCL) is one of the main approaches to solving Quantified Boolean Formulas (QBF). Cube-learning is employed in this approach to ensure that true formulas can be verified. Dependency Schemes help to detect spurious dependencies that are implied by the variable ordering in the quantifier prefix of QBFs but are not essential for constructing (counter)models. This detection can provably shorten refutations in specific proof systems, and is expected to speed up runs of QBF solvers. The simplest underlying proof system [BeyersdorffBöhm-LMCS2023], formalises the reasoning in the QCDCL approach on false formulas, when neither cube-learning nor dependency schemes is used. The work of [BöhmPeitlBeyersdorff-AI2024] further incorporates cube-learning. The work of [ChoudhuryMahajan-JAR2024] incorporates a limited use of dependency schemes, but without cube-learning. In this work, proof systems underlying the reasoning of QCDCL solvers which use cube learning, and which use dependency schemes at all stages, are formalised. Sufficient conditions for soundness and completeness are presented, and it is shown that using the standard and reflexive resolution path dependency schemes (𝙳^{std} and 𝙳^{rrs}) to relax the decision order provably shortens refutations. When the decisions are restricted to follow quantification order, but dependency schemes are used in propagation and learning, in conjunction with cube-learning, the resulting proof systems using the dependency schemes 𝙳^{std} and 𝙳^{rrs} are investigated in detail and their relative strengths are analysed.
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Abhimanyu Choudhury and Meena Mahajan. On the Interplay of Cube Learning and Dependency Schemes in {QCDCL} Proof Systems. In 45th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 360, pp. 25:1-25:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{choudhury_et_al:LIPIcs.FSTTCS.2025.25,
  author =	{Choudhury, Abhimanyu and Mahajan, Meena},
  title =	{{On the Interplay of Cube Learning and Dependency Schemes in \{QCDCL\} Proof Systems}},
  booktitle =	{45th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2025)},
  pages =	{25:1--25:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-406-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{360},
  editor =	{Aiswarya, C. and Mehta, Ruta and Roy, Subhajit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2025.25},
  URN =		{urn:nbn:de:0030-drops-251062},
  doi =		{10.4230/LIPIcs.FSTTCS.2025.25},
  annote =	{Keywords: QBF, CDCL, Resolution, Dependency schemes}
}
Document
Survey
DOI: 10.4230/TGDK.3.2.1
Resilience in Knowledge Graph Embeddings

Authors: Arnab Sharma, N'Dah Jean Kouagou, and Axel-Cyrille Ngonga Ngomo

Published in: TGDK, Volume 3, Issue 2 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 2

Abstract
In recent years, knowledge graphs have gained interest and witnessed widespread applications in various domains, such as information retrieval, question-answering, recommendation systems, amongst others. Large-scale knowledge graphs to this end have demonstrated their utility in effectively representing structured knowledge. To further facilitate the application of machine learning techniques, knowledge graph embedding models have been developed. Such models can transform entities and relationships within knowledge graphs into vectors. However, these embedding models often face challenges related to noise, missing information, distribution shift, adversarial attacks, etc. This can lead to sub-optimal embeddings and incorrect inferences, thereby negatively impacting downstream applications. While the existing literature has focused so far on adversarial attacks on KGE models, the challenges related to the other critical aspects remain unexplored. In this paper, we, first of all, give a unified definition of resilience, encompassing several factors such as generalisation, in-distribution generalization, distribution adaption, and robustness. After formalizing these concepts for machine learning in general, we define them in the context of knowledge graphs. To find the gap in the existing works on resilience in the context of knowledge graphs, we perform a systematic survey, taking into account all these aspects mentioned previously. Our survey results show that most of the existing works focus on a specific aspect of resilience, namely robustness. After categorizing such works based on their respective aspects of resilience, we discuss the challenges and future research directions.
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Arnab Sharma, N'Dah Jean Kouagou, and Axel-Cyrille Ngonga Ngomo. Resilience in Knowledge Graph Embeddings. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 2, pp. 1:1-1:38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{sharma_et_al:TGDK.3.2.1,
  author =	{Sharma, Arnab and Kouagou, N'Dah Jean and Ngomo, Axel-Cyrille Ngonga},
  title =	{{Resilience in Knowledge Graph Embeddings}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:38},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.2.1},
  URN =		{urn:nbn:de:0030-drops-248117},
  doi =		{10.4230/TGDK.3.2.1},
  annote =	{Keywords: Knowledge graphs, Resilience, Robustness}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.12
Large Multi-Modal Model Cartographic Map Comprehension for Textual Locality Georeferencing

Authors: Kalana Wijegunarathna, Kristin Stock, and Christopher B. Jones

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
Millions of biological sample records collected in the last few centuries archived in natural history collections are un-georeferenced. Georeferencing complex locality descriptions associated with these collection samples is a highly labour-intensive task collection agencies struggle with. None of the existing automated methods exploit maps that are an essential tool for georeferencing complex relations. We present preliminary experiments and results of a novel method that exploits multi-modal capabilities of recent Large Multi-Modal Models (LMM). This method enables the model to visually contextualize spatial relations it reads in the locality description. We use a grid-based approach to adapt these auto-regressive models for this task in a zero-shot setting. Our experiments conducted on a small manually annotated dataset show impressive results for our approach (∼1 km Average distance error) compared to uni-modal georeferencing with Large Language Models and existing georeferencing tools. The paper also discusses the findings of the experiments in light of an LMM’s ability to comprehend fine-grained maps. Motivated by these results, a practical framework is proposed to integrate this method into a georeferencing workflow.
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Kalana Wijegunarathna, Kristin Stock, and Christopher B. Jones. Large Multi-Modal Model Cartographic Map Comprehension for Textual Locality Georeferencing. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 12:1-12:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{wijegunarathna_et_al:LIPIcs.GIScience.2025.12,
  author =	{Wijegunarathna, Kalana and Stock, Kristin and Jones, Christopher B.},
  title =	{{Large Multi-Modal Model Cartographic Map Comprehension for Textual Locality Georeferencing}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{12:1--12:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.12},
  URN =		{urn:nbn:de:0030-drops-238412},
  doi =		{10.4230/LIPIcs.GIScience.2025.12},
  annote =	{Keywords: Large Multi-Modal Models, Large Language Models, LLM, Georeferencing, Natural History collections}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.10
Geovicla: Automated Classification of Interactive Web-Based Geovisualizations

Authors: Phil Hüffer, Auriol Degbelo, and Benjamin Risse

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
The exponential growth of interactive geovisualizations on the Web has underscored the need for automated techniques to enhance their findability. In this paper, we present the Geovicla dataset (2.5K instances), constructed through the harvesting and manual labelling of webpages from a broad range of domains. The webpages are categorized into three groups: "interactive visualisation", "interactive geovisualisation" and "`no interactive visualisation". Using this dataset, we compared three approaches for interactive (geo)visualization classification: (i) a heuristic-based approach (i.e. using manually derived rules), (ii) a feature-engineering approach (i.e. hand-crafted feature vectors combined with machine learning classifiers) and (iii) an embedding-based approach (i.e. automatically generated large language model (LLM) embeddings with machine learning classifiers). The results indicate that LLM embeddings, when used in conjunction with a multilayer perceptron, form a promising combination, achieving up to 74% accuracy for multiclass classification and 75% for binary classification. The dataset and the insights gained from our empirical comparison offer valuable resources for GIScience researchers aiming to enhance the discoverability of interactive geovisualizations.
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Phil Hüffer, Auriol Degbelo, and Benjamin Risse. Geovicla: Automated Classification of Interactive Web-Based Geovisualizations. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 10:1-10:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{huffer_et_al:LIPIcs.GIScience.2025.10,
  author =	{H\"{u}ffer, Phil and Degbelo, Auriol and Risse, Benjamin},
  title =	{{Geovicla: Automated Classification of Interactive Web-Based Geovisualizations}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{10:1--10:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.10},
  URN =		{urn:nbn:de:0030-drops-238397},
  doi =		{10.4230/LIPIcs.GIScience.2025.10},
  annote =	{Keywords: spatial information search, geovisualization search, findable interactive geovisualization, webpage classification}
}
Document
DOI: 10.4230/LIPIcs.WABI.2025.10
DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs

Authors: Ali Ghaffaari, Alexander Schönhuth, and Tobias Marschall

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)

Abstract
Determining the distance between two loci within a genomic region is a recurrent operation in various tasks in computational genomics. A notable example of this task arises in paired-end read mapping as a form of validation of distances between multiple alignments. While straightforward for a single genome, graph-based reference structures render the operation considerably more involved. Given the sheer number of such queries in a typical read mapping experiment, an efficient algorithm for answering distance queries is crucial. In this paper, we introduce DiVerG, a compact data structure as well as a fast and scalable algorithm, for constructing distance indexes for general sequence graphs on multi-core CPU and many-core GPU architectures. DiVerG is based on PairG [Jain et al., 2019], but overcomes the limitations of PairG by exploiting the extensive potential for improvements in terms of scalability and space efficiency. As a consequence, DiVerG can process substantially larger datasets, such as whole human genomes, which are unmanageable by PairG. DiVerG offers faster index construction time and consistently faster query time with gains proportional to the size of the underlying compact data structure. We demonstrate that our method performs favorably on multiple real datasets at various scales. DiVerG achieves superior performance over PairG; e.g. resulting to 2.5-4x speed-up in query time, 44-340x smaller index size, and 3-50x faster construction time for the genome graph of the MHC region, as a particularly variable region of the human genome. The implementation is available at: https://github.com/cartoonist/diverg
Cite as

Ali Ghaffaari, Alexander Schönhuth, and Tobias Marschall. DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 10:1-10:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ghaffaari_et_al:LIPIcs.WABI.2025.10,
  author =	{Ghaffaari, Ali and Sch\"{o}nhuth, Alexander and Marschall, Tobias},
  title =	{{DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{10:1--10:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.10},
  URN =		{urn:nbn:de:0030-drops-239369},
  doi =		{10.4230/LIPIcs.WABI.2025.10},
  annote =	{Keywords: Sequence graph, distance index, read mapping, sparse matrix}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.34
DynamicSAT: Dynamic Configuration Tuning for SAT Solving

Authors: Zhengyuan Shi, Wentao Jiang, Xindi Zhang, Jin Luo, Yun Liang, Zhufei Chu, and Qiang Xu

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

Abstract
Boolean Satisfiability (SAT) problem serves as a foundation for solving numerous real-world challenges. As problem complexity increases, so does the demand for sophisticated SAT solvers, which incorporate a variety of heuristics tailored to optimize performance for specific problem instances. However, a major limitation persists: a configuration that performs well on one instance may lead to inefficiencies on others. While previous approaches to automatic algorithm configuration set parameters prior to runtime, they fail to adapt to the dynamic evolution of problem characteristics during the solving process. We introduce DynamicSAT, a novel SAT solver framework that dynamically tunes configuration parameters during solving process. By adjusting parameters on-the-fly, DynamicSAT adapts to changes arising from clause learning, elimination, and other transformations, thus improving efficiency and robustness across diverse SAT instances. We demonstrate that DynamicSAT achieves significant performance gains over the state-of-the-art solver on 2024 SAT Competition Benchmark.
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Zhengyuan Shi, Wentao Jiang, Xindi Zhang, Jin Luo, Yun Liang, Zhufei Chu, and Qiang Xu. DynamicSAT: Dynamic Configuration Tuning for SAT Solving. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 34:1-34:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{shi_et_al:LIPIcs.CP.2025.34,
  author =	{Shi, Zhengyuan and Jiang, Wentao and Zhang, Xindi and Luo, Jin and Liang, Yun and Chu, Zhufei and Xu, Qiang},
  title =	{{DynamicSAT: Dynamic Configuration Tuning for SAT Solving}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{34:1--34:23},
  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.2025.34},
  URN =		{urn:nbn:de:0030-drops-238952},
  doi =		{10.4230/LIPIcs.CP.2025.34},
  annote =	{Keywords: Boolean satisfiability problem, configuration tuning, multi-armed bandit}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.3
Solving the Agile Earth Observation Satellite Scheduling Problem with CP and Local Search

Authors: Valentin Antuori, Damien T. Wojtowicz, and Emmanuel Hebrard

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

Abstract
The increasing hunger for remote sensing data fuels a boom in satellite imagery, leading to larger agile Earth observation satellite (AEOS) constellations. Therefore, instances of the AEOS scheduling problem (AEOSSP) has become harder to solve. As most existing approaches to solve AEOSSP are designed for a single spacecraft or smaller constellations in mind, they are not tailored to the need of our industrial partner that is about to launch a constellation of 20 AEOSs. Hence, we designed a local search solver able to schedule observations and downloads at such a scale. It relies on solving a series of sub-problems as travelling salesman problem with time windows (TSPTW), first greedily, then using a CP-SAT exact solver in order to find a solution when the greedy insertion fails. Lastly, it schedules downloads and enforces memory constraints with greedy algorithms. Experiments were carried out on instances from the literature as well as generated instances from a simulator we designed. Our experiments show that using CP to solve the sub-problem significantly improve the solutions, and overall our method is slightly better than state-of-the-art approaches.
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Valentin Antuori, Damien T. Wojtowicz, and Emmanuel Hebrard. Solving the Agile Earth Observation Satellite Scheduling Problem with CP and Local Search. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 3:1-3:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{antuori_et_al:LIPIcs.CP.2025.3,
  author =	{Antuori, Valentin and Wojtowicz, Damien T. and Hebrard, Emmanuel},
  title =	{{Solving the Agile Earth Observation Satellite Scheduling Problem with CP and Local Search}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{3:1--3:22},
  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.2025.3},
  URN =		{urn:nbn:de:0030-drops-238647},
  doi =		{10.4230/LIPIcs.CP.2025.3},
  annote =	{Keywords: Local Search, Greedy Algorithms, Aerospace Applications}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.28
SLS-Enhanced Core-Boosted Linear Search for Anytime Maximum Satisfiability

Authors: Ole Lübke and Jeremias Berg

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

Abstract
Maximum Satisfiability (MaxSAT), the constraint paradigm of minimizing a linear expression over Boolean (0-1) variables subject to a set of propositional clauses, is today used for solving NP-hard combinatorial optimization problems in various domains. Especially anytime MaxSAT solvers that compute low-cost solutions within a limited available computational time have significantly improved in recent years. Such solvers can be divided into SAT-based methods that use sophisticated reasoning, and stochastic local search (SLS) methods that heuristically explore the search space. The two are complementary; roughly speaking, SLS struggles with finding feasible solutions, and SAT-based methods with minimizing cost. Consequently, most state-of-the-art anytime MaxSAT solvers run SLS before a SAT-based algorithm with minimal communication between the two. In this paper, we aim to harness the complementary strengths of SAT-based, and SLS approaches in the context of anytime MaxSAT. More precisely, we describe several ways to enhance the performance of the so-called core-boosted linear search algorithm for anytime MaxSAT with SLS techniques. Core-boosted linear search is a three-phase algorithm where each phase uses different types of reasoning. Beyond MaxSAT, core-boosted search has also been successful in the related paradigms of pseudo-boolean optimization and constraint programming. We describe how an SLS approach to MaxSAT can be tightly integrated with all three phases of the algorithm, resulting in non-trivial information exchange in both directions between the SLS algorithm and the reasoning methods. We evaluate our techniques on standard benchmarks from the latest MaxSAT Evaluation and demonstrate that our techniques can noticeably improve on implementations of core-boosted search and SLS.
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Ole Lübke and Jeremias Berg. SLS-Enhanced Core-Boosted Linear Search for Anytime Maximum Satisfiability. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 28:1-28:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{lubke_et_al:LIPIcs.CP.2025.28,
  author =	{L\"{u}bke, Ole and Berg, Jeremias},
  title =	{{SLS-Enhanced Core-Boosted Linear Search for Anytime Maximum Satisfiability}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{28:1--28:20},
  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.2025.28},
  URN =		{urn:nbn:de:0030-drops-238897},
  doi =		{10.4230/LIPIcs.CP.2025.28},
  annote =	{Keywords: Maximum Satisfiability, MaxSAT, SAT, SLS, Anytime Optimization}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.22
Learning to Bound for Maximum Common Subgraph Algorithms

Authors: Buddhi W. Kothalawala, Henning Koehler, and Qing Wang

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

Abstract
Identifying the maximum common subgraph between two graphs is a computationally challenging NP-hard problem. While the McSplit algorithm represents a state-of-the-art approach within a branch-and-bound (BnB) framework, several extensions have been proposed to enhance its vertex pair selection strategy, often utilizing reinforcement learning techniques. Nonetheless, the quality of the upper bound remains a critical factor in accelerating the search process by effectively pruning unpromising branches. This research introduces a novel, more restrictive upper bound derived from a detailed analysis of the McSplit algorithm’s generated partitions. To enhance the effectiveness of this bound, we propose a reinforcement learning approach that strategically directs computational effort towards the most promising regions within the search space.
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Buddhi W. Kothalawala, Henning Koehler, and Qing Wang. Learning to Bound for Maximum Common Subgraph Algorithms. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 22:1-22:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{kothalawala_et_al:LIPIcs.CP.2025.22,
  author =	{Kothalawala, Buddhi W. and Koehler, Henning and Wang, Qing},
  title =	{{Learning to Bound for Maximum Common Subgraph Algorithms}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{22:1--22:18},
  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.2025.22},
  URN =		{urn:nbn:de:0030-drops-238837},
  doi =		{10.4230/LIPIcs.CP.2025.22},
  annote =	{Keywords: Combinatorial Search, Branch and Bound, Graph Theory}
}
Document
DOI: 10.4230/OASIcs.Manzini.3
BWT for String Collections

Authors: Davide Cenzato, Zsuzsanna Lipták, Nadia Pisanti, Giovanna Rosone, and Marinella Sciortino

Published in: OASIcs, Volume 131, The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday (2025)

Abstract
We survey the different methods used for extending the BWT to collections of strings, following largely [Cenzato and Lipták, CPM 2022, Bioinformatics 2024]. We analyze the specific aspects and combinatorial properties of the resulting BWT variants and give a categorization of publicly available tools for computing the BWT of string collections. We show how the specific method used impacts on the resulting transform, including the number of runs, and on the dynamicity of the transform with respect to adding or removing strings from the collection. We then focus on the number of runs of these BWT variants and present the optimal BWT introduced in [Cenzato et al., DCC 2023], which implements an algorithm originally proposed by [Bentley et al., ESA 2020] to minimize the number of BWT-runs. We also discuss several recent heuristics and study their impact on the compression of biological sequences. We conclude with an overview of the applications and the impact of the BWT of string collections in bioinformatics.
Cite as

Davide Cenzato, Zsuzsanna Lipták, Nadia Pisanti, Giovanna Rosone, and Marinella Sciortino. BWT for String Collections. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 3:1-3:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{cenzato_et_al:OASIcs.Manzini.3,
  author =	{Cenzato, Davide and Lipt\'{a}k, Zsuzsanna and Pisanti, Nadia and Rosone, Giovanna and Sciortino, Marinella},
  title =	{{BWT for String Collections}},
  booktitle =	{The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday},
  pages =	{3:1--3:29},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-390-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{131},
  editor =	{Ferragina, Paolo and Gagie, Travis and Navarro, Gonzalo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Manzini.3},
  URN =		{urn:nbn:de:0030-drops-239113},
  doi =		{10.4230/OASIcs.Manzini.3},
  annote =	{Keywords: Burrows-Wheeler transform, Extended Burrows-Wheeler transform, compressed text indexes, text compression, string collections, bioinformatics}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.3
Problem Partitioning via Proof Prefixes

Authors: Zachary Battleman, Joseph E. Reeves, and Marijn J. H. Heule

Published in: LIPIcs, Volume 341, 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)

Abstract
Satisfiability solvers have been instrumental in tackling hard problems, including mathematical challenges that require years of computation. A key obstacle in efficiently solving such problems lies in effectively partitioning them into many, frequently millions of subproblems. Existing automated partitioning techniques, primarily based on lookahead methods, perform well on some instances but fail to generate effective partitions for many others. This paper introduces a powerful partitioning approach that leverages prefixes of proofs derived from conflict-driven clause-learning solvers. This method enables non-experts to harness the power of massively parallel SAT solving for their problems. We also propose a semantically-driven partitioning technique tailored for problems with large cardinality constraints, which frequently arise in optimization tasks. We evaluate our methods on diverse benchmarks, including combinatorial problems and formulas from SAT and MaxSAT competitions. Our results demonstrate that these techniques outperform existing partitioning strategies in many cases, offering improved scalability and efficiency.
Cite as

Zachary Battleman, Joseph E. Reeves, and Marijn J. H. Heule. Problem Partitioning via Proof Prefixes. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 3:1-3:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{battleman_et_al:LIPIcs.SAT.2025.3,
  author =	{Battleman, Zachary and Reeves, Joseph E. and Heule, Marijn J. H.},
  title =	{{Problem Partitioning via Proof Prefixes}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{3:1--3:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-381-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{341},
  editor =	{Berg, Jeremias and Nordstr\"{o}m, Jakob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2025.3},
  URN =		{urn:nbn:de:0030-drops-237378},
  doi =		{10.4230/LIPIcs.SAT.2025.3},
  annote =	{Keywords: Satisfiability solving, parallel computing, problem partitioning}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.19
An Application of SAT Solvers in Integer Programming Games

Authors: Pravesh Koirala, Aditya Shrey, and Forrest Laine

Published in: LIPIcs, Volume 341, 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)

Abstract
Integer programming games (IPGs) are a popular game-theoretic tool to model an array of games where each player has a discrete strategy set. These games arise in important domains such as economics, transportation, cybersecurity, etc., but solving them is non-trivial as it is known that checking for the existence of pure Nash equilibria in an IPG is Σ₂^p-complete. Recent works have proposed a class of relaxed solution concepts for IPGs called locally optimal integer solutions (LOIS) and shown it to be an efficient alternative for pure Nash equilibria. While LOIS are significantly simpler to compute, they still do not scale when solved using traditional mathematical solvers, especially when high-quality solutions are desired. In this paper, we apply commercially available SAT solvers to find LOIS in IPGs. We investigate efficient encodings for a cybersecurity game and compare solution times when using SAT solvers vs mathematical program solvers. We also investigate the application of SAT solvers in graph games using a graph interdiction example and compare against the obtained LOI solutions against existing heuristics-based solutions. Our results indicate that with appropriate encodings, large-scale IPGs can be solved much more efficiently using SAT solvers. We also show that SAT solvers can be applied to graph games in conjunction with LOIS for obtaining high-quality solutions. Our results emphasize the potential of SAT solvers combined with LOIS to solve significant game theory problems.
Cite as

Pravesh Koirala, Aditya Shrey, and Forrest Laine. An Application of SAT Solvers in Integer Programming Games. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 19:1-19:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{koirala_et_al:LIPIcs.SAT.2025.19,
  author =	{Koirala, Pravesh and Shrey, Aditya and Laine, Forrest},
  title =	{{An Application of SAT Solvers in Integer Programming Games}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{19:1--19:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-381-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{341},
  editor =	{Berg, Jeremias and Nordstr\"{o}m, Jakob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2025.19},
  URN =		{urn:nbn:de:0030-drops-237534},
  doi =		{10.4230/LIPIcs.SAT.2025.19},
  annote =	{Keywords: Game Theory, Integer Programming Games, SAT Solvers, Local Solutions, Graph Games}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.23
Symbolic Conflict Analysis in Pseudo-Boolean Optimization

Authors: Robert Nieuwenhuis, Albert Oliveras, Enric Rodríguez-Carbonell, and Rui Zhao

Published in: LIPIcs, Volume 341, 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)

Abstract
In the the last two decades, a lot of effort has been devoted to the development of satisfiability-checking tools for a variety of SAT-related problems. However, most of these tools lack optimization capabilities. That is, instead of finding any solution, one is sometimes interested in a solution that is best according to some criterion. Pseudo-Boolean solvers can be used to deal with optimization by successively solving a series of problems that contain an additional pseudo-Boolean constraint expressing that a better solution is required. A key point for the success of this simple approach is that lemmas that are learned for one problem can be reused for subsequent ones. In this paper we go one step further and show how, by using a simple symbolic conflict analysis procedure, not only can lemmas be reused between problems but also strengthened, thus further pruning the search space traversal. In addition, we show how this technique automatically allows one to infer upper bounds in maximization problems, thus giving an estimation of how far the solver is from finding an optimal solution. Experimental results with our PB solver reveal that (i) this technique is indeed effective in practice, providing important speedups in problems where several solutions are found and (ii) on problems with very few solutions, where the impact of our technique is limited, its overhead is negligible.
Cite as

Robert Nieuwenhuis, Albert Oliveras, Enric Rodríguez-Carbonell, and Rui Zhao. Symbolic Conflict Analysis in Pseudo-Boolean Optimization. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 23:1-23:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{nieuwenhuis_et_al:LIPIcs.SAT.2025.23,
  author =	{Nieuwenhuis, Robert and Oliveras, Albert and Rodr{\'\i}guez-Carbonell, Enric and Zhao, Rui},
  title =	{{Symbolic Conflict Analysis in Pseudo-Boolean Optimization}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{23:1--23:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-381-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{341},
  editor =	{Berg, Jeremias and Nordstr\"{o}m, Jakob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2025.23},
  URN =		{urn:nbn:de:0030-drops-237579},
  doi =		{10.4230/LIPIcs.SAT.2025.23},
  annote =	{Keywords: SAT, Pseudo-Boolean Optimization, Conflict Analysis}
}
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