@inproceedings{suzgun-etal-2026-string2string,
title = "string2string Studio: An Interactive, In-Browser Platform for String-to-String Algorithms",
author = "Suzgun, Mirac and
Zou, James and
Shieber, Stuart and
Jurafsky, Dan",
editor = "Agrawal, Sweta and
Abad, Alberto",
booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.emnlp-demos.42/",
pages = "435--444",
ISBN = "979-8-89176-461-3",
abstract = "We present string2string Studio, an in-browser workbench for string-to-string analysis across natural language processing, computational biology, and the digital humanities. The system integrates six modules (alignment, distance, similarity, search, generation metrics, and BLAST homology search) and operates at character, word, token, line, and residue levels. Its C++ algorithms compile to WebAssembly, so core operations run locally by default without installation or data upload. The interface reports scores with their evidence (alignments, edit paths, metric matches, search hits, and homology traces), making methods inspectable, debuggable, and comparable on shared inputs. Internal benchmarks show speedups of up to 2,500x over the Python predecessor, faster global/local alignment than a general-purpose native C aligner, and exact agreement with independent references under declared settings. For homology search, the scoped client-side blastn path closely matches NCBI BLAST+ rankings and statistics under matched parameters. A curated showcase and Learn mode package canonical algorithms and metrics as reusable demonstrations. string2string Studio is open-source and freely available at string2string.org."
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%0 Conference Proceedings
%T string2string Studio: An Interactive, In-Browser Platform for String-to-String Algorithms
%A Suzgun, Mirac
%A Zou, James
%A Shieber, Stuart
%A Jurafsky, Dan
%Y Agrawal, Sweta
%Y Abad, Alberto
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-461-3
%F suzgun-etal-2026-string2string
%X We present string2string Studio, an in-browser workbench for string-to-string analysis across natural language processing, computational biology, and the digital humanities. The system integrates six modules (alignment, distance, similarity, search, generation metrics, and BLAST homology search) and operates at character, word, token, line, and residue levels. Its C++ algorithms compile to WebAssembly, so core operations run locally by default without installation or data upload. The interface reports scores with their evidence (alignments, edit paths, metric matches, search hits, and homology traces), making methods inspectable, debuggable, and comparable on shared inputs. Internal benchmarks show speedups of up to 2,500x over the Python predecessor, faster global/local alignment than a general-purpose native C aligner, and exact agreement with independent references under declared settings. For homology search, the scoped client-side blastn path closely matches NCBI BLAST+ rankings and statistics under matched parameters. A curated showcase and Learn mode package canonical algorithms and metrics as reusable demonstrations. string2string Studio is open-source and freely available at string2string.org.
%U https://aclanthology.org/2026.emnlp-demos.42/
%P 435-444
Markdown (Informal)
[string2string Studio: An Interactive, In-Browser Platform for String-to-String Algorithms](https://aclanthology.org/2026.emnlp-demos.42/) (Suzgun et al., EMNLP 2026)
ACL