3 Search Results for "Palmer, Zachary"

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.
Cite as

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)

Copy BibTex To Clipboard

@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.ECOOP.2016.19
Higher-Order Demand-Driven Program Analysis

Authors: Zachary Palmer and Scott F. Smith

Published in: LIPIcs, Volume 56, 30th European Conference on Object-Oriented Programming (ECOOP 2016)

Abstract
We explore a novel approach to higher-order program analysis that brings ideas of on-demand lookup from first-order CFL-reachability program analyses to higher-order programs. The analysis needs to produce only a control-flow graph; it can derive all other information including values of variables directly from the graph. Several challenges had to be overcome, including how to build the control-flow graph on-the-fly and how to deal with non-local variables in functions. The resulting analysis is flow- and context-sensitive with a provable polynomial-time bound. The analysis is formalized and proved correct and terminating, and an initial implementation is described.
Cite as

Zachary Palmer and Scott F. Smith. Higher-Order Demand-Driven Program Analysis. In 30th European Conference on Object-Oriented Programming (ECOOP 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 56, pp. 19:1-19:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

Copy BibTex To Clipboard

@InProceedings{palmer_et_al:LIPIcs.ECOOP.2016.19,
  author =	{Palmer, Zachary and Smith, Scott F.},
  title =	{{Higher-Order Demand-Driven Program Analysis}},
  booktitle =	{30th European Conference on Object-Oriented Programming (ECOOP 2016)},
  pages =	{19:1--19:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-014-9},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{56},
  editor =	{Krishnamurthi, Shriram and Lerner, Benjamin S.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2016.19},
  URN =		{urn:nbn:de:0030-drops-61132},
  doi =		{10.4230/LIPIcs.ECOOP.2016.19},
  annote =	{Keywords: functional programming, program analysis, polynomial-time, demand-driven, flow-sensitive, context-sensitive}
}
Document
DOI: 10.4230/DARTS.2.1.9
Higher-Order Demand-Driven Program Analysis (Artifact)

Authors: Leandro Facchinetti, Zachary Palmer, and Scott F. Smith

Published in: DARTS, Volume 2, Issue 1, Special Issue of the 30th European Conference on Object-Oriented Programming (ECOOP 2016)

Abstract
This artifact is a proof-of-concept implementation of DDPA, an on-demand program analysis for higher-order functional programs. The implementation, written in OCaml, includes a parser, evaluator, and DDPA analysis for the language defined in the companion paper (including the proper record semantics extension). The analysis may be performed using different levels of precision as specified by the user and is capable of rendering the control flow graphs and pushdown systems using the GraphViz language DOT. This artifact was used to verify the conclusions of the companion paper and produces visualizations matching those figures in the companion paper's overview.
Cite as

Leandro Facchinetti, Zachary Palmer, and Scott F. Smith. Higher-Order Demand-Driven Program Analysis (Artifact). In Special Issue of the 30th European Conference on Object-Oriented Programming (ECOOP 2016). Dagstuhl Artifacts Series (DARTS), Volume 2, Issue 1, pp. 9:1-9:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

Copy BibTex To Clipboard

@Article{facchinetti_et_al:DARTS.2.1.9,
  author =	{Facchinetti, Leandro and Palmer, Zachary and Smith, Scott F.},
  title =	{{Higher-Order Demand-Driven Program Analysis (Artifact)}},
  pages =	{9:1--9:2},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2016},
  volume =	{2},
  number =	{1},
  editor =	{Facchinetti, Leandro and Palmer, Zachary and Smith, Scott F.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.2.1.9},
  URN =		{urn:nbn:de:0030-drops-61304},
  doi =		{10.4230/DARTS.2.1.9},
  annote =	{Keywords: program analysis, polynomial, demand-driven, flow-sensitive, context-sensitive}
}
  • Refine by Type
  • 3 Document/PDF
  • 1 Document/HTML

  • Refine by Publication Year
  • 1 2025
  • 2 2016

  • Refine by Author
  • 2 Palmer, Zachary
  • 2 Smith, Scott F.
  • 1 Bernstein, Abraham
  • 1 Facchinetti, Leandro
  • 1 Ruosch, Florian
  • Show More...

  • Refine by Series/Journal
  • 1 LIPIcs
  • 1 DARTS
  • 1 TGDK

  • Refine by Classification
  • 1 Computing methodologies → Information extraction
  • 1 Computing methodologies → Language resources
  • 1 Computing methodologies → Semantic networks
  • 1 Information systems → Graph-based database models

  • Refine by Keyword
  • 2 context-sensitive
  • 2 demand-driven
  • 2 flow-sensitive
  • 2 program analysis
  • 1 Argument Mining
  • 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