7 Search Results for "Baker, Ryan S."

Document
DOI: 10.4230/LIPIcs.ITCS.2026.37
New Algebrization Barriers to Circuit Lower Bounds via Communication Complexity of Missing-String

Authors: Lijie Chen, Yang Hu, and Hanlin Ren

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

Abstract
The algebrization barrier, proposed by Aaronson and Wigderson (STOC '08, ToCT '09), captures the limitations of many complexity-theoretic techniques based on arithmetization. Notably, several circuit lower bounds that overcome the relativization barrier (Buhrman-Fortnow-Thierauf, CCC '98; Vinodchandran, TCS '05; Santhanam, STOC '07, SICOMP '09) remain subject to the algebrization barrier. In this work, we establish several new algebrization barriers to circuit lower bounds by studying the communication complexity of the following problem, called XOR-Missing-String: For m < 2^{n/2}, Alice gets a list of m strings x₁, … , x_m ∈ {0, 1}ⁿ, Bob gets a list of m strings y₁, … , y_m ∈ {0, 1}ⁿ, and the goal is to output a string s ∈ {0, 1}ⁿ that is not equal to x_i⊕ y_j for any i, j ∈ [m]. 1) We construct an oracle A₁ and its multilinear extension A₁̃ such that PostBPE^{A₁̃} has linear-size A₁-oracle circuits on infinitely many input lengths. That is, proving PostBPE ̸ ⊆ i.o.- SIZE[O(n)] requires non-algebrizing techniques. This barrier follows from a PostBPP communication lower bound for XOR-Missing-String. This is in contrast to the well-known algebrizing lower bound MA_E (⊆ PostBPE) ̸ ⊆ P/_poly. 2) We construct an oracle A₂ and its multilinear extension A₂̃ such that BPE^{A₂̃} has linear-size A₂-oracle circuits on all input lengths. Previously, a similar barrier was demonstrated by Aaronson and Wigderson, but in their result, A₂̃ is only a multiquadratic extension of A₂. Our results show that communication complexity is more useful than previously thought for proving algebrization barriers, as Aaronson and Wigderson wrote that communication-based barriers were "more contrived". This serves as an example of how XOR-Missing-String forms new connections between communication lower bounds and algebrization barriers. 3) Finally, we study algebrization barriers to circuit lower bounds for MA_E. Buhrman, Fortnow, and Thierauf proved a sub-half-exponential circuit lower bound for MA_E via algebrizing techniques. Toward understanding whether the half-exponential bound can be improved, we define a natural subclass of MA_E that includes their hard MA_E language, and prove the following result: For every super-half-exponential function h(n), we construct an oracle A₃ and its multilinear extension A₃̃ such that this natural subclass of MA_E^{A₃̃} has h(n)-size A₃-oracle circuits on all input lengths. This suggests that half-exponential might be the correct barrier for MA_E circuit lower bounds w.r.t. algebrizing techniques.
Cite as

Lijie Chen, Yang Hu, and Hanlin Ren. New Algebrization Barriers to Circuit Lower Bounds via Communication Complexity of Missing-String. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 37:1-37:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{chen_et_al:LIPIcs.ITCS.2026.37,
  author =	{Chen, Lijie and Hu, Yang and Ren, Hanlin},
  title =	{{New Algebrization Barriers to Circuit Lower Bounds via Communication Complexity of Missing-String}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{37:1--37:20},
  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.2026.37},
  URN =		{urn:nbn:de:0030-drops-253246},
  doi =		{10.4230/LIPIcs.ITCS.2026.37},
  annote =	{Keywords: circuit lower bound, algebrization barrier, missing string, communication complexity}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2026.95
Identity Testing for Circuits with Exponentiation Gates

Authors: Jiatu Li and Mengdi Wu

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

Abstract
Motivated by practical applications in the design of optimization compilers for neural networks, we initiated the study of identity testing problems for arithmetic circuits augmented with exponentiation gates that compute the real function x↦ e^x. These circuits compute real functions of form P(→x)/P'(→x), where both P(→x) and P'(→x) are exponential polynomials ∑_{i = 1}^k f_i(→x)⋅ exp((g_i(→x))/(h_i(→x))), for polynomials f_i(→x),g_i(→x), and h_i(→x). We formalize a black-box query model over finite fields for this class of circuits, which is mathematical simple and reflects constraints faced by real-world neural network compilers. We proved that a simple and efficient randomized identity testing algorithm achieves perfect completeness and non-trivial soundness. Concurrent with our work, the algorithm has been implemented in the optimization compiler Mirage by Wu et al. (OSDI 2025), demonstrating promising empirical performance in both efficiency and soundness error. Finally, we propose a number-theoretic conjecture under which our algorithm is sound with high probability.
Cite as

Jiatu Li and Mengdi Wu. Identity Testing for Circuits with Exponentiation Gates. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 95:1-95:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{li_et_al:LIPIcs.ITCS.2026.95,
  author =	{Li, Jiatu and Wu, Mengdi},
  title =	{{Identity Testing for Circuits with Exponentiation Gates}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{95:1--95:22},
  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.2026.95},
  URN =		{urn:nbn:de:0030-drops-253821},
  doi =		{10.4230/LIPIcs.ITCS.2026.95},
  annote =	{Keywords: Polynomial Identity Testing, Exponential Polynomials}
}
Document
DOI: 10.4230/OASIcs.SpaceCHI.2025.20
Navigating Exoplanetary Systems in Augmented Reality: Preliminary Insights on ExoAR

Authors: Bryson Lawton, Frank Maurer, and Daniel Zielasko

Published in: OASIcs, Volume 130, Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)

Abstract
With thousands of exoplanets now confirmed by space missions such as NASA’s Kepler and TESS, scientific interest and public curiosity about these distant worlds continue to grow. However, current visualization tools for exploring exoplanetary systems often lack sufficient scientific accuracy or interactive features, limiting their educational effectiveness and analytical utility. To help address this gap, we developed ExoAR, an augmented reality tool designed to offer immersive, scientifically sound visualizations of all known exoplanetary systems using data directly sourced from NASA’s Exoplanet Archive. By leveraging augmented reality’s strengths, ExoAR enables users to immerse themselves in interactive, dynamic 3D models of these planetary systems with data-driven representations of planets and their host stars. The application also allows users to adjust various visualization scales independently, a capability designed to aid comprehension of comparative astronomical properties such as orbital mechanics, planetary sizes, and stellar classifications. To begin assessing ExoAR’s potential as an educational and analytical tool and inform future iterations, a pilot user study was conducted. Its findings indicate that participants found ExoAR improved user engagement and spatial understanding compared to NASA’s Eyes on Exoplanets application, a non-immersive exoplanetary system visualization tool. This work-in-progress paper presents these early insights, acknowledges current system limitations, and outlines future directions for more rigorously evaluating and further improving ExoAR’s capabilities for both educational and scientific communities.
Cite as

Bryson Lawton, Frank Maurer, and Daniel Zielasko. Navigating Exoplanetary Systems in Augmented Reality: Preliminary Insights on ExoAR. In Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025). Open Access Series in Informatics (OASIcs), Volume 130, pp. 20:1-20:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{lawton_et_al:OASIcs.SpaceCHI.2025.20,
  author =	{Lawton, Bryson and Maurer, Frank and Zielasko, Daniel},
  title =	{{Navigating Exoplanetary Systems in Augmented Reality: Preliminary Insights on ExoAR}},
  booktitle =	{Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025)},
  pages =	{20:1--20:13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-384-3},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{130},
  editor =	{Bensch, Leonie and Nilsson, Tommy and Nisser, Martin and Pataranutaporn, Pat and Schmidt, Albrecht and Sumini, Valentina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SpaceCHI.2025.20},
  URN =		{urn:nbn:de:0030-drops-240106},
  doi =		{10.4230/OASIcs.SpaceCHI.2025.20},
  annote =	{Keywords: Immersive Analytics, Data Visualization, Astronomy, Astrophysics, Exoplanet, Augmented Reality, AR}
}
Document
DOI: 10.4230/OASIcs.ICPEC.2025.4
Can Open Large Language Models Catch Vulnerabilities?

Authors: Diogo Gaspar Lopes, Tiago Espinha Gasiba, Sathwik Amburi, and Maria Pinto-Albuquerque

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)

Abstract
As Large Language Models (LLMs) become increasingly integrated into secure software development workflows, a critical question remains unanswered: can these models not only detect insecure code but also reliably classify vulnerabilities according to standardized taxonomies? In this work, we conduct a systematic evaluation of three state-of-the-art LLMs - Llama3, Codestral, and Deepseek R1 - using a carefully filtered subset of the Big-Vul dataset annotated with eight representative Common Weakness Enumeration categories. Adopting a closed-world classification setup, we assess each model’s performance in both identifying the presence of vulnerabilities and mapping them to the correct CWE label. Our findings reveal a sharp contrast between high detection rates and markedly poor classification accuracy, with frequent overgeneralization and misclassification. Moreover, we analyze model-specific biases and common failure modes, shedding light on the limitations of current LLMs in performing fine-grained security reasoning.These insights are especially relevant in educational contexts, where LLMs are being adopted as learning aids despite their limitations. A nuanced understanding of their behaviour is essential to prevent the propagation of misconceptions among students. Our results expose key challenges that must be addressed before LLMs can be reliably deployed in security-sensitive environments.
Cite as

Diogo Gaspar Lopes, Tiago Espinha Gasiba, Sathwik Amburi, and Maria Pinto-Albuquerque. Can Open Large Language Models Catch Vulnerabilities?. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 4:1-4:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{gasparlopes_et_al:OASIcs.ICPEC.2025.4,
  author =	{Gaspar Lopes, Diogo and Espinha Gasiba, Tiago and Amburi, Sathwik and Pinto-Albuquerque, Maria},
  title =	{{Can Open Large Language Models Catch Vulnerabilities?}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{4:1--4:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.4},
  URN =		{urn:nbn:de:0030-drops-240340},
  doi =		{10.4230/OASIcs.ICPEC.2025.4},
  annote =	{Keywords: Large Language Models (LLMs), Secure Coding, CWE Classification, Machine Learning, Software Vulnerability Detection, Artificial Intelligence, Code Analysis, Big-Vul Dataset}
}
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.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)

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@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/OASIcs.LDK.2019.25
Predicting Math Success in an Online Tutoring System Using Language Data and Click-Stream Variables: A Longitudinal Analysis

Authors: Scott Crossley, Shamya Karumbaiah, Jaclyn Ocumpaugh, Matthew J. Labrum, and Ryan S. Baker

Published in: OASIcs, Volume 70, 2nd Conference on Language, Data and Knowledge (LDK 2019)

Abstract
Previous studies have demonstrated strong links between students' linguistic knowledge, their affective language patterns and their success in math. Other studies have shown that demographic and click-stream variables in online learning environments are important predictors of math success. This study builds on this research in two ways. First, it combines linguistics and click-stream variables along with demographic information to increase prediction rates for math success. Second, it examines how random variance, as found in repeated participant data, can explain math success beyond linguistic, demographic, and click-stream variables. The findings indicate that linguistic, demographic, and click-stream factors explained about 14% of the variance in math scores. These variables mixed with random factors explained about 44% of the variance.
Cite as

Scott Crossley, Shamya Karumbaiah, Jaclyn Ocumpaugh, Matthew J. Labrum, and Ryan S. Baker. Predicting Math Success in an Online Tutoring System Using Language Data and Click-Stream Variables: A Longitudinal Analysis. In 2nd Conference on Language, Data and Knowledge (LDK 2019). Open Access Series in Informatics (OASIcs), Volume 70, pp. 25:1-25:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{crossley_et_al:OASIcs.LDK.2019.25,
  author =	{Crossley, Scott and Karumbaiah, Shamya and Ocumpaugh, Jaclyn and Labrum, Matthew J. and Baker, Ryan S.},
  title =	{{Predicting Math Success in an Online Tutoring System Using Language Data and Click-Stream Variables: A Longitudinal Analysis}},
  booktitle =	{2nd Conference on Language, Data and Knowledge (LDK 2019)},
  pages =	{25:1--25:13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-105-4},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{70},
  editor =	{Eskevich, Maria and de Melo, Gerard and F\"{a}th, Christian and McCrae, John P. and Buitelaar, Paul and Chiarcos, Christian and Klimek, Bettina and Dojchinovski, Milan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2019.25},
  URN =		{urn:nbn:de:0030-drops-103895},
  doi =		{10.4230/OASIcs.LDK.2019.25},
  annote =	{Keywords: Natural language processing, math education, online tutoring systems, text analytics, click-stream variables}
}
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