26 Search Results for "Vu, Van"

Document
DOI: 10.4230/DagRep.15.7.53
(Actual) Neurosymbolic AI: Combining Deep Learning and Knowledge Graphs (Dagstuhl Seminar 25291)

Authors: Pascal Hitzler, Cogan Shimizu, Daria Stepanova, and Frank van Harmelen

Published in: Dagstuhl Reports, Volume 15, Issue 7 (2026)

Abstract
In the past decade, both deep learning (DL) and knowledge graphs (KGs) have seen astonishing growth and groundbreaking milestones – DL due to newly available resources (e.g., accessibility of (modern) web scale data), previously un-scalable techniques (e.g., transformers), and modern hardware; KGs due to successful standardization, web-scale integration, and previously un-scalable techniques for querying and inference. This has brought new and increased interest to both fields, and especially in how they can complement each other. % This report documents the program and the outcomes of Dagstuhl Seminar 25291 "(Actual) Neurosymbolic AI: Combining Deep Learning and Knowledge Graphs". This Dagstuhl Seminar brought 34 internationally recognized experts together to examine the gap between deep learning and knowledge graphs, and architect their integration: neurosymbolic AI.
Cite as

Pascal Hitzler, Cogan Shimizu, Daria Stepanova, and Frank van Harmelen. (Actual) Neurosymbolic AI: Combining Deep Learning and Knowledge Graphs (Dagstuhl Seminar 25291). In Dagstuhl Reports, Volume 15, Issue 7, pp. 53-123, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@Article{hitzler_et_al:DagRep.15.7.53,
  author =	{Hitzler, Pascal and Shimizu, Cogan and Stepanova, Daria and van Harmelen, Frank},
  title =	{{(Actual) Neurosymbolic AI: Combining Deep Learning and Knowledge Graphs (Dagstuhl Seminar 25291)}},
  pages =	{53--123},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2026},
  volume =	{15},
  number =	{7},
  editor =	{Hitzler, Pascal and Shimizu, Cogan and Stepanova, Daria and van Harmelen, Frank},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.53},
  URN =		{urn:nbn:de:0030-drops-257675},
  doi =		{10.4230/DagRep.15.7.53},
  annote =	{Keywords: deep learning, knowledge graphs, neurosymbolic ai}
}
Document
DOI: 10.4230/LIPIcs.STACS.2026.79
Mind the Gap. Doubling Constant Parametrization of Weighted Problems: TSP, Max-Cut, and More

Authors: Mihail Stoian

Published in: LIPIcs, Volume 364, 43rd International Symposium on Theoretical Aspects of Computer Science (STACS 2026)

Abstract
Despite much research, hard weighted problems still resist super-polynomial improvements over their textbook solution. On the other hand, the unweighted versions of these problems have recently witnessed the sought-after speedups. Currently, the only way to repurpose the algorithm of the unweighted version for the weighted version is to employ a polynomial embedding of the input weights. This, however, introduces a pseudo-polynomial factor into the running time, which becomes impractical for arbitrarily weighted instances. In this paper, we introduce a new way to repurpose the algorithm of the unweighted problem. Specifically, we show that the time complexity of several well-known NP-hard problems operating over the (min, +) and (max, +) semirings, such as TSP, Weighted Max-Cut, and Edge-Weighted k-Clique, is proportional to that of their unweighted versions when the set of input weights has small doubling. We achieve this by a meta-algorithm that converts the input weights into polynomially bounded integers using the recent constructive Freiman’s theorem by Randolph and Węgrzycki [ESA 2024] before applying the polynomial embedding.
Cite as

Mihail Stoian. Mind the Gap. Doubling Constant Parametrization of Weighted Problems: TSP, Max-Cut, and More. In 43rd International Symposium on Theoretical Aspects of Computer Science (STACS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 364, pp. 79:1-79:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{stoian:LIPIcs.STACS.2026.79,
  author =	{Stoian, Mihail},
  title =	{{Mind the Gap. Doubling Constant Parametrization of Weighted Problems: TSP, Max-Cut, and More}},
  booktitle =	{43rd International Symposium on Theoretical Aspects of Computer Science (STACS 2026)},
  pages =	{79:1--79:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-412-3},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{364},
  editor =	{Mahajan, Meena and Manea, Florin and McIver, Annabelle and Thắng, Nguy\~{ê}n Kim},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2026.79},
  URN =		{urn:nbn:de:0030-drops-255680},
  doi =		{10.4230/LIPIcs.STACS.2026.79},
  annote =	{Keywords: doubling constant parametrization, weighted problems, traveling salesman, weighted max-cut, edge-weighted k-clique}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2026.12
Semi-Random Graphs, Robust Asymmetry, and Reconstruction

Authors: Julian Asilis, Xi Chen, Dutch Hansen, and Shang-Hua Teng

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)

Abstract
The Graph Reconstruction Conjecture famously posits that any undirected graph on at least three vertices is determined up to isomorphism by its family of (unlabeled) induced subgraphs. At present, the conjecture admits partial resolutions of two types: 1) casework-based demonstrations of reconstructibility for families of graphs satisfying certain structural properties, and 2) probabilistic arguments establishing reconstructibility of random graphs by leveraging average-case phenomena. While results in the first category capture the worst-case nature of the conjecture, they play a limited role in understanding the general case. Results in the second category address much larger graph families, but it remains unclear how heavily the necessary arguments rely on optimistic distributional properties. Drawing on the algorithmic notions of smoothed and semi-random analysis, we study the robustness of what are arguably the two most fundamental properties in this latter line of work: asymmetry and uniqueness of subgraphs. Notably, we find that various natural semi-random graph distributions exhibit these properties asymptotically, much like their Erdős-Rényi counterparts. In particular, Bollobás [Bollob{á}s, 1990] demonstrated that almost all Erdős-Rényi random graphs G = (V, E) ∼ G(n, p) enjoy the property that their induced subgraphs on n - Θ(1) vertices are asymmetric and mutually non-isomorphic, for 1 - p, p = Ω(log(n) / n). As our primary result, we demonstrate that this property is robust against perturbation - even when an adversary is permitted to add/remove each vertex pair in V^{(2)} with (independent) arbitrarily large constant probability. Exploiting this result, we derive asymptotic characterizations of asymmetry in random graphs with large planted structure and bounded adversarial corruptions, along with improved bounds on the probability mass of nonreconstructible graphs in G(n, p).
Cite as

Julian Asilis, Xi Chen, Dutch Hansen, and Shang-Hua Teng. Semi-Random Graphs, Robust Asymmetry, and Reconstruction. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 12:1-12:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{asilis_et_al:LIPIcs.ITCS.2026.12,
  author =	{Asilis, Julian and Chen, Xi and Hansen, Dutch and Teng, Shang-Hua},
  title =	{{Semi-Random Graphs, Robust Asymmetry, and Reconstruction}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{12:1--12:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.12},
  URN =		{urn:nbn:de:0030-drops-252993},
  doi =		{10.4230/LIPIcs.ITCS.2026.12},
  annote =	{Keywords: Graph reconstruction, random graphs}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2026.85
Recovering Communities in Structured Random Graphs

Authors: Michael Kapralov, Luca Trevisan, and Weronika Wrzos-Kaminska

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)

Abstract
The problem of recovering planted community structure in random graphs has received a lot of attention in the literature on the stochastic block model, where the input is a random graph in which edges crossing between different communities appear with smaller probability than edges induced by communities. The communities themselves form a collection of vertex-disjoint sparse cuts in the expected graph, and can be recovered, often exactly, from a sample as long as a separation condition on the intra- and inter-community edge probabilities is satisfied. In this paper, we ask whether the presence of a large number of overlapping sparsest cuts in the expected graph still allows recovery. For example, the d-dimensional hypercube graph admits d distinct (balanced) sparsest cuts, one for every coordinate. Can these cuts be identified given a random sample of the edges of the hypercube where each edge is present independently with some probability p ∈ (0, 1)? We show that this is the case, in a very strong sense: the sparsest balanced cut in a sample of the hypercube at rate p = Clog d/d for a sufficiently large constant C is 1/poly(d)-close to a coordinate cut with high probability. This is asymptotically optimal and allows approximate recovery of all d cuts simultaneously. Furthermore, for an appropriate sample of hypercube-like graphs recovery can be made exact. The proof is essentially a strong hypercube cut sparsification bound that combines a theorem of Friedgut, Kalai and Naor on boolean functions whose Fourier transform concentrates on the first level of the Fourier spectrum with Karger’s cut counting argument.
Cite as

Michael Kapralov, Luca Trevisan, and Weronika Wrzos-Kaminska. Recovering Communities in Structured Random Graphs. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 85:1-85:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{kapralov_et_al:LIPIcs.ITCS.2026.85,
  author =	{Kapralov, Michael and Trevisan, Luca and Wrzos-Kaminska, Weronika},
  title =	{{Recovering Communities in Structured Random Graphs}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{85:1--85:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.85},
  URN =		{urn:nbn:de:0030-drops-253727},
  doi =		{10.4230/LIPIcs.ITCS.2026.85},
  annote =	{Keywords: Hypercube graphs, Community detection, Fourier analysis of Boolean functions}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2026.57
Anti-Concentration for the Unitary Haar Measure and Applications to Random Quantum Circuits

Authors: Bill Fefferman, Soumik Ghosh, and Wei Zhan

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)

Abstract
We prove a Carbery-Wright style anti-concentration inequality for the unitary Haar measure, by showing that the probability of a polynomial in the entries of a random unitary falling into an ε range is at most a polynomial in ε. Using it, we show that the scrambling speed of a random quantum circuit is lower bounded: Namely, every input qubit has an influence that is at least inverse exponential in depth, on any output qubit touched by its lightcone. Our result on scrambling speed works with high probability over the choice of a circuit from an ensemble, as opposed to just working in expectation. As an application, we give the first polynomial-time algorithm for learning log-depth random quantum circuits with Haar random gates up to polynomially small diamond distance, given oracle access to the circuit. Other applications of this new scrambling speed lower bound include: - An optimal Ω(log ε^{-1}) depth lower bound for ε-approximate unitary designs on any circuit architecture; - A polynomial-time quantum algorithm that computes the depth of a bounded-depth circuit, given oracle access to the circuit. Our learning and depth-testing algorithms apply to architectures defined over any geometric dimension, and can be generalized to a wide class of architectures with good lightcone properties.
Cite as

Bill Fefferman, Soumik Ghosh, and Wei Zhan. Anti-Concentration for the Unitary Haar Measure and Applications to Random Quantum Circuits. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 57:1-57:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{fefferman_et_al:LIPIcs.ITCS.2026.57,
  author =	{Fefferman, Bill and Ghosh, Soumik and Zhan, Wei},
  title =	{{Anti-Concentration for the Unitary Haar Measure and Applications to Random Quantum Circuits}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{57:1--57:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.57},
  URN =		{urn:nbn:de:0030-drops-253443},
  doi =		{10.4230/LIPIcs.ITCS.2026.57},
  annote =	{Keywords: Haar measure, anti-concentration, random quanytum circuit, learning}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.91
Near-Optimal Differentially Private Graph Algorithms via the Multidimensional AboveThreshold Mechanism

Authors: Laxman Dhulipala, Monika Henzinger, George Z. Li, Quanquan C. Liu, A. R. Sricharan, and Leqi Zhu

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
Many differentially private and classical non-private graph algorithms rely crucially on determining whether some property of each vertex meets a threshold. For example, for the k-core decomposition problem, the classic peeling algorithm iteratively removes a vertex if its induced degree falls below a threshold. The sparse vector technique (SVT) is generally used to transform non-private threshold queries into private ones with only a small additive loss in accuracy. However, a naive application of SVT in the graph setting leads to an amplification of the error by a factor of n due to composition, as SVT is applied to every vertex. In this paper, we resolve this problem by formulating a novel generalized sparse vector technique which we call the Multidimensional AboveThreshold (MAT) Mechanism which generalizes SVT (applied to vectors with one dimension) to vectors with multiple dimensions. When applied to vectors with n dimensions, we solve a number of important graph problems with better bounds than previous work. Specifically, we apply our MAT mechanism to obtain a set of improved bounds for a variety of problems including k-core decomposition, densest subgraph, low out-degree ordering, and vertex coloring. We give a tight local edge differentially private (LEDP) algorithm for k-core decomposition that results in an approximation with O(ε^{-1} log n) additive error and no multiplicative error in O(n) rounds. We also give a new (2+η)-factor multiplicative, O(ε^{-1} log n) additive error algorithm in O(log² n) rounds for any constant η > 0. Both of these results are asymptotically tight against our new lower bound of Ω(log n) for any constant-factor approximation algorithm for k-core decomposition. Our new algorithms for k-core decomposition also directly lead to new algorithms for the related problems of densest subgraph and low out-degree ordering. Finally, we give novel LEDP differentially private defective coloring algorithms that use number of colors given in terms of the arboricity of the graph.
Cite as

Laxman Dhulipala, Monika Henzinger, George Z. Li, Quanquan C. Liu, A. R. Sricharan, and Leqi Zhu. Near-Optimal Differentially Private Graph Algorithms via the Multidimensional AboveThreshold Mechanism. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 91:1-91:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{dhulipala_et_al:LIPIcs.ESA.2025.91,
  author =	{Dhulipala, Laxman and Henzinger, Monika and Li, George Z. and Liu, Quanquan C. and Sricharan, A. R. and Zhu, Leqi},
  title =	{{Near-Optimal Differentially Private Graph Algorithms via the Multidimensional AboveThreshold Mechanism}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{91:1--91:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.91},
  URN =		{urn:nbn:de:0030-drops-245601},
  doi =		{10.4230/LIPIcs.ESA.2025.91},
  annote =	{Keywords: differential privacy, abovethreshold, densest subgraph}
}
Document
DOI: 10.4230/LIPIcs.ESA.2025.9
MorphisHash: Improving Space Efficiency of ShockHash for Minimal Perfect Hashing

Authors: Stefan Hermann

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract
A minimal perfect hash function (MPHF) maps a set of n keys to unique positions {1, …, n}. Representing an MPHF requires at least log₂(e)≈ 1.443 bits per key. ShockHash is a technique to construct an MPHF and requires just slightly more space. It gives each key two random candidate positions. If each key can be mapped to one of its two candidate positions such that there is exactly one key mapped to each position, then an MPHF is found. If not, ShockHash repeats the process with a new set of random candidate positions. ShockHash has to store how many repetitions were required and for each key to which of the two candidate positions it is mapped. However, when a given set of candidate positions can be used as MPHF then there is not only one but multiple ways of mapping the keys to one of their candidate positions such that the mapping results in an MPHF. This redundancy makes up for the majority of the remaining space overhead in ShockHash. In this paper, we present MorphisHash which almost completely eliminates this redundancy. Our theoretical result is that MorphisHash saves Θ(ln(n)) bits in expectation compared to ShockHash. This corresponds to a factor of 20 less space overhead in practice. Just like ShockHash, MorphisHash can be used as a building block within RecSplit to obtain MorphisHash-RS. When compared for same space consumption, MorphisHash-RS can be constructed up to 21 times faster than ShockHash-RS. The technique to accomplish this might be of a more general interest to compress data structures.
Cite as

Stefan Hermann. MorphisHash: Improving Space Efficiency of ShockHash for Minimal Perfect Hashing. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 9:1-9:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{hermann:LIPIcs.ESA.2025.9,
  author =	{Hermann, Stefan},
  title =	{{MorphisHash: Improving Space Efficiency of ShockHash for Minimal Perfect Hashing}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{9:1--9:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.9},
  URN =		{urn:nbn:de:0030-drops-244779},
  doi =		{10.4230/LIPIcs.ESA.2025.9},
  annote =	{Keywords: compressed data structure, perfect hashing, random graph, pseudoforest, component}
}
Document
DOI: 10.4230/OASIcs.Programming.2025.20
On the Effectiveness of Interpreter-Guided Compiler Testing

Authors: Federico Lochbaum and Guillermo Polito

Published in: OASIcs, Volume 134, Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025)

Abstract
Guaranteeing that a compiler behaves correctly is a complex task often approached through test generation and fuzzing. Compiler test generation must not only ensure that a compiler generates code that does not break, but also that it implements the programming language semantics. Recently, interpreter-guided test generation has been proposed to test JIT compilers: Concolic-execution on the interpreter yields test cases for the language semantics which are then validated between differential testing of the interpreter and compiler. In previous work, this solution has been shown to find interpreter/compiler differences. However, little has been said about the effectiveness and the solution limits. In this paper we study the behavior of this technique, to shed light on future improvements and research. We experiment with this technique on the JIT compiler for the Pharo programming language, on two different backends: ARMv7 and x86. We explore how effective the solution is in terms of compiler coverage and its limitations, and we discuss how future research can overcome them. Moreover, we investigate how this technique combined with random constraint mutations increases backend compiler coverage.
Cite as

Federico Lochbaum and Guillermo Polito. On the Effectiveness of Interpreter-Guided Compiler Testing. In Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025). Open Access Series in Informatics (OASIcs), Volume 134, pp. 20:1-20:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{lochbaum_et_al:OASIcs.Programming.2025.20,
  author =	{Lochbaum, Federico and Polito, Guillermo},
  title =	{{On the Effectiveness of Interpreter-Guided Compiler Testing}},
  booktitle =	{Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025)},
  pages =	{20:1--20:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-382-9},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{134},
  editor =	{Edwards, Jonathan and Perera, Roly and Petricek, Tomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Programming.2025.20},
  URN =		{urn:nbn:de:0030-drops-243040},
  doi =		{10.4230/OASIcs.Programming.2025.20},
  annote =	{Keywords: Virtual Machines, Concolic Testing, JIT compilers, interpreters, Differential Testing, Constraint Mutations, Compiler Coverage}
}
Document
DOI: 10.4230/LIPIcs.SAT.2025.8
Certifying Projected Knowledge Compilation

Authors: Randal E. Bryant, Yong Kiam Tan, and Marijn J. H. Heule

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

Abstract
Knowledge compilers convert Boolean formulas, given in conjunctive normal form (CNF), into representations that enable efficient evaluation of unweighted and weighted model counts, as well as a variety of other useful properties. With projected knowledge compilation, the generated representation describes the restriction of the formula to a designated set of data variables, with the remaining ones eliminated by existential quantification. Projected knowledge compilation has applications in a variety of domains, including formal verification and synthesis. This paper describes a formally verified proof framework for certifying the output of a projected knowledge compiler. It builds on an earlier clausal proof framework for certifying the output of a standard knowledge compiler. Extending the framework to projected compilation requires a method to represent Skolem assignments, describing how the quantified variables can be assigned, given an assignment for the data variables. We do so by extending the representation generated by the knowledge compiler to also encode Skolem assignments. We also refine the earlier framework, moving beyond purely clausal proofs to enable scaling certification to larger formulas. We present experimental results obtained by making small modifications to the D4 projected knowledge compiler and extensions of our earlier proof generator. We detail a soundness argument stating that a compiler output that passes our certifier is logically equivalent to the quantified input formula; the soundness argument has been formally validated using the HOL4 proof assistant. The checker also ensures that the compiler output satisfies the properties required for efficient unweighted and weighted model counting. We have developed two proof checkers for the certification framework: one written in C and designed for high performance and one written in CakeML and formally verified in HOL4.
Cite as

Randal E. Bryant, Yong Kiam Tan, and Marijn J. H. Heule. Certifying Projected Knowledge Compilation. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 8:1-8:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{bryant_et_al:LIPIcs.SAT.2025.8,
  author =	{Bryant, Randal E. and Tan, Yong Kiam and Heule, Marijn J. H.},
  title =	{{Certifying Projected Knowledge Compilation}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{8:1--8:22},
  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.2025.8},
  URN =		{urn:nbn:de:0030-drops-237422},
  doi =		{10.4230/LIPIcs.SAT.2025.8},
  annote =	{Keywords: Knowledge Compilation, Propositional model counting, Proof checking}
}
Document
DOI: 10.4230/LIPIcs.CCC.2025.11
Switching Graph Matrix Norm Bounds: From i.i.d. to Random Regular Graphs

Authors: Jeff Xu

Published in: LIPIcs, Volume 339, 40th Computational Complexity Conference (CCC 2025)

Abstract
In this work, we give novel spectral norm bounds for graph matrix on inputs being random regular graphs. Graph matrix is a family of random matrices with entries given by polynomial functions of the underlying input. These matrices have been known to be the backbone for the analysis of various average-case algorithms and hardness. Previous investigations of such matrices are largely restricted to the Erdős-Rényi model, and tight matrix norm bounds on regular graphs are only known for specific examples. We unite these two lines of investigations, and give the first result departing from the Erdős-Rényi setting in the full generality of graph matrices. We believe our norm bound result would enable a simple transfer of spectral analysis for average-case algorithms and hardness between these two distributions of random graphs. As an application of our spectral norm bounds, we show that higher-degree Sum-of-Squares lower bounds for the independent set problem on Erdős-Rényi random graphs can be switched into lower bounds on random d-regular graphs. Our main conceptual insight is that existing Sum-of-Squares lower bounds analysis based on moment methods are surprisingly robust, and amenable for a light-weight translation. Our result is the first to address the general open question of analyzing higher-degree Sum-of-Squares on random regular graphs.
Cite as

Jeff Xu. Switching Graph Matrix Norm Bounds: From i.i.d. to Random Regular Graphs. In 40th Computational Complexity Conference (CCC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 339, pp. 11:1-11:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{xu:LIPIcs.CCC.2025.11,
  author =	{Xu, Jeff},
  title =	{{Switching Graph Matrix Norm Bounds: From i.i.d. to Random Regular Graphs}},
  booktitle =	{40th Computational Complexity Conference (CCC 2025)},
  pages =	{11:1--11:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-379-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{339},
  editor =	{Srinivasan, Srikanth},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2025.11},
  URN =		{urn:nbn:de:0030-drops-237054},
  doi =		{10.4230/LIPIcs.CCC.2025.11},
  annote =	{Keywords: Semidefinite programming, random matrices, average-case complexity}
}
Document
DOI: 10.4230/LIPIcs.SEA.2025.1
Polymorphic Cycle Basis in a Sequence of Graphs to Analyze the Structural Evolution of a Molecular Dynamic Trajectory

Authors: Ylène Aboulfath, Dominique Barth, Thierry Mautor, Dimitri Watel, and Marc-Antoine Weisser

Published in: LIPIcs, Volume 338, 23rd International Symposium on Experimental Algorithms (SEA 2025)

Abstract
Molecular dynamics analysis is a fundamental topic in chemistry, in particular the study of the formation and dissolution of hydrogen bonds over time. The dynamics of these bonds create and break cycles which are crucial to the structure of the molecules. The challenge in cycle analysis is twofold: there is an exponential number of cycles, and some cycles are very close. We introduce a graph-based approach using minimum cycle bases to assist in molecular dynamics analysis. Given a set of graphs representing a molecule trajectory, we determine, for each graph, a minimum cycle basis and construct a graph of cycles which represents the cycles of minimum bases and their interactions. Then, we aggregate all information from these graphs of cycles into a polygraph. Each vertex of the polygraph represents a class of cycles appearing in different minimum bases and playing equivalent roles in the trajectory. This paper introduces our approach, establishes the complexity of associated problems, and suggests an implementation. Simulations are conducted on both real and generated data to evaluate the performance of our approach.
Cite as

Ylène Aboulfath, Dominique Barth, Thierry Mautor, Dimitri Watel, and Marc-Antoine Weisser. Polymorphic Cycle Basis in a Sequence of Graphs to Analyze the Structural Evolution of a Molecular Dynamic Trajectory. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 1:1-1:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{aboulfath_et_al:LIPIcs.SEA.2025.1,
  author =	{Aboulfath, Yl\`{e}ne and Barth, Dominique and Mautor, Thierry and Watel, Dimitri and Weisser, Marc-Antoine},
  title =	{{Polymorphic Cycle Basis in a Sequence of Graphs to Analyze the Structural Evolution of a Molecular Dynamic Trajectory}},
  booktitle =	{23rd International Symposium on Experimental Algorithms (SEA 2025)},
  pages =	{1:1--1:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-375-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{338},
  editor =	{Mutzel, Petra and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.1},
  URN =		{urn:nbn:de:0030-drops-232399},
  doi =		{10.4230/LIPIcs.SEA.2025.1},
  annote =	{Keywords: Graph theory, Cycle basis, Molecular analysis}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2025.70
Tiling Random Regular Graphs Efficiently

Authors: Sahar Diskin, Ilay Hoshen, and Maksim Zhukovskii

Published in: LIPIcs, Volume 334, 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)

Abstract
We show that for every ε > 0 there exists a sufficiently large d₀ ∈ ℕ such that for every d ≥ d₀, whp the random d-regular graph G(n,d) contains a T-factor for every tree T on at most (1-ε)d/log d vertices. This is best possible since, for large enough integer d, whp G(n,d) does not contain a ((1+ε)d)/(log d)-star-factor. Our method gives a randomised algorithm which whp finds said T-factor and whose expected running time is O(n^{1+o(1)}), as well as an efficient deterministic counterpart.
Cite as

Sahar Diskin, Ilay Hoshen, and Maksim Zhukovskii. Tiling Random Regular Graphs Efficiently. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 70:1-70:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{diskin_et_al:LIPIcs.ICALP.2025.70,
  author =	{Diskin, Sahar and Hoshen, Ilay and Zhukovskii, Maksim},
  title =	{{Tiling Random Regular Graphs Efficiently}},
  booktitle =	{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},
  pages =	{70:1--70:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-372-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{334},
  editor =	{Censor-Hillel, Keren and Grandoni, Fabrizio and Ouaknine, Jo\"{e}l and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.70},
  URN =		{urn:nbn:de:0030-drops-234477},
  doi =		{10.4230/LIPIcs.ICALP.2025.70},
  annote =	{Keywords: Random regular graphs, Tree tilings}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2025.13
FuzzFlesh: Randomised Testing of Decompilers via Control Flow Graph-Based Program Generation

Authors: Amber Gorzynski and Alastair F. Donaldson

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
Decompilation is the process of translating compiled code into high-level code. Control flow recovery is a challenging part of the process. "Misdecompilations" can occur, whereby the decompiled code does not accurately represent the semantics of the compiled code, despite it being syntactically valid. This is problematic because it can mislead users who are trying to reason about the program. We present CFG-based program generation: a novel approach to randomised testing that aims to improve the control flow recovery of decompilers. CFG-based program generation involves randomly generating control flow graphs (CFGs) and paths through each graph. Inspired by prior work in the domain of GPU computing, (CFG, path) pairs are "fleshed" into test programs. Each program is decompiled and recompiled. The test oracle verifies whether the actual runtime path through the graph matches the expected path. Any difference in the execution paths after recompilation indicates a possible misdecompilation. A key benefit of this approach is that it is largely independent of the source and target languages in question because it is focused on control flow. The approach is therefore applicable to numerous decompilation settings. The trade-off resulting from the focus on control flow is that misdecompilation bugs that do not relate to control flow (e.g. bugs that involve specific arithmetic operations) are out of scope. We have implemented this approach in FuzzFlesh, an open-source randomised testing tool. FuzzFlesh can be easily configured to target a variety of low-level languages and decompiler toolchains because most of the CFG and path generation process is language-independent. At present, FuzzFlesh supports testing decompilation of Java bytecode, .NET assembly and x86 machine code. In addition to program generation, FuzzFlesh also includes an automated test-case reducer that operates on the CFG rather than the low-level program, which means that it can be applied to any of the target languages. We present a large experimental campaign applying FuzzFlesh to a variety of decompilers, leading to the discovery of 12 previously-unknown bugs across two language formats, six of which have been fixed. We present experiments comparing our generic FuzzFlesh tool to two state-of-the-art decompiler testing tools targeted at specific languages. As expected, the coverage our generic FuzzFlesh tool achieves on a given decompiler is lower than the coverage achieved by a tool specifically designed for the input format of that decompiler. However, due to its focus on control flow, FuzzFlesh is able to cover sections of control flow recovery code that the targeted tools cannot reach, and identify control flow related bugs that the targeted tools miss.
Cite as

Amber Gorzynski and Alastair F. Donaldson. FuzzFlesh: Randomised Testing of Decompilers via Control Flow Graph-Based Program Generation. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 13:1-13:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{gorzynski_et_al:LIPIcs.ECOOP.2025.13,
  author =	{Gorzynski, Amber and Donaldson, Alastair F.},
  title =	{{FuzzFlesh: Randomised Testing of Decompilers via Control Flow Graph-Based Program Generation}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{13:1--13:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.13},
  URN =		{urn:nbn:de:0030-drops-233062},
  doi =		{10.4230/LIPIcs.ECOOP.2025.13},
  annote =	{Keywords: Decompiler, Reverse Engineering, Control Flow, Software Testing, Fuzzing}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2025.10
Bottom-Up Synthesis of Memory Mutations with Separation Logic

Authors: Kasra Ferdowsi and Hila Peleg

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
Programming-by-Example (PBE) is the paradigm of program synthesis specified via input-output pairs. It is commonly used because examples are easy to provide and collect from the environment. A popular optimization for enumerative synthesis with examples is Observational Equivalence (OE), which groups programs into equivalence classes according to their evaluation on example inputs. Current formulations of OE, however, are severely limited by the assumption that the synthesizer’s target language contains only pure components with no side-effects, either enforcing this in their target language, or ignoring it, leading to an incorrect enumeration. This limits their ability to use realistic component sets. We address this limitation by borrowing from Separation Logic, which can compositionally reason about heap mutations. We reformulate PBE using a restricted Separation Logic: Concrete Heap Separation Logic (CHSL), transforming the search for programs into a proof search in CHSL. This lets us perform bottom-up enumerative synthesis without the need for expert-provided annotations or domain-specific inferences, but with three key advantages: we (i) preserve correctness in the presence of memory-mutating operations, (ii) compact the search space by representing many concrete programs as one under CHSL, and (iii) perform a provably correct OE-reduction. We present SObEq (Side-effects in OBservational EQuivalence), a bottom-up enumerative algorithm that, given a PBE task, searches for its CHSL derivation. The SObEq algorithm is proved correct with no purity assumptions: we show it is guaranteed to lose no solutions. We also evaluate our implementation of SObEq on benchmarks from the literature and online sources, and show that it produces high-quality results quickly.
Cite as

Kasra Ferdowsi and Hila Peleg. Bottom-Up Synthesis of Memory Mutations with Separation Logic. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 10:1-10:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{ferdowsi_et_al:LIPIcs.ECOOP.2025.10,
  author =	{Ferdowsi, Kasra and Peleg, Hila},
  title =	{{Bottom-Up Synthesis of Memory Mutations with Separation Logic}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{10:1--10:32},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.10},
  URN =		{urn:nbn:de:0030-drops-233036},
  doi =		{10.4230/LIPIcs.ECOOP.2025.10},
  annote =	{Keywords: Program synthesis, observational equivalence}
}
Document
Survey
DOI: 10.4230/TGDK.3.1.3
Uncertainty Management in the Construction of Knowledge Graphs: A Survey

Authors: Lucas Jarnac, Yoan Chabot, and Miguel Couceiro

Published in: TGDK, Volume 3, Issue 1 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 1

Abstract
Knowledge Graphs (KGs) are a major asset for companies thanks to their great flexibility in data representation and their numerous applications, e.g., vocabulary sharing, Q&A or recommendation systems. To build a KG, it is a common practice to rely on automatic methods for extracting knowledge from various heterogeneous sources. However, in a noisy and uncertain world, knowledge may not be reliable and conflicts between data sources may occur. Integrating unreliable data would directly impact the use of the KG, therefore such conflicts must be resolved. This could be done manually by selecting the best data to integrate. This first approach is highly accurate, but costly and time-consuming. That is why recent efforts focus on automatic approaches, which represent a challenging task since it requires handling the uncertainty of extracted knowledge throughout its integration into the KG. We survey state-of-the-art approaches in this direction and present constructions of both open and enterprise KGs. We then describe different knowledge extraction methods and discuss downstream tasks after knowledge acquisition, including KG completion using embedding models, knowledge alignment, and knowledge fusion in order to address the problem of knowledge uncertainty in KG construction. We conclude with a discussion on the remaining challenges and perspectives when constructing a KG taking into account uncertainty.
Cite as

Lucas Jarnac, Yoan Chabot, and Miguel Couceiro. Uncertainty Management in the Construction of Knowledge Graphs: A Survey. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 1, pp. 3:1-3:48, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@Article{jarnac_et_al:TGDK.3.1.3,
  author =	{Jarnac, Lucas and Chabot, Yoan and Couceiro, Miguel},
  title =	{{Uncertainty Management in the Construction of Knowledge Graphs: A Survey}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:48},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.1.3},
  URN =		{urn:nbn:de:0030-drops-233733},
  doi =		{10.4230/TGDK.3.1.3},
  annote =	{Keywords: Knowledge reconciliation, Uncertainty, Heterogeneous sources, Knowledge graph construction}
}
  • Refine by Type
  • 26 Document/PDF
  • 22 Document/HTML

  • Refine by Publication Year
  • 5 2026
  • 16 2025
  • 1 2024
  • 1 2023
  • 2 2022
  • Show More...

  • Refine by Author
  • 4 van Harmelen, Frank
  • 2 Li, George Z.
  • 1 Aboulfath, Ylène
  • 1 Alman, Josh
  • 1 Asilis, Julian
  • Show More...

  • Refine by Series/Journal
  • 19 LIPIcs
  • 1 OASIcs
  • 1 LITES
  • 1 TGDK
  • 4 DagRep

  • Refine by Classification
  • 5 Mathematics of computing → Random graphs
  • 3 Computing methodologies → Artificial intelligence
  • 3 Computing methodologies → Machine learning
  • 3 Mathematics of computing → Probability and statistics
  • 3 Theory of computation → Automated reasoning
  • Show More...

  • Refine by Keyword
  • 1 Abstraction
  • 1 Boolean function analysis
  • 1 Chernoff bounds
  • 1 Cognitive Science
  • 1 Community detection
  • Show More...

Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2026 Schloss Dagstuhl – LZI GmbH Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact