JCT 2026 - SemEval Task 5

Chava Laufer; Batel Turjeman; Chaya Liebeskind

JCT 2026 - SemEval Task 5

Chava Laufer, Batel Turjeman, Chaya Liebeskind

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Abstract

The system integrates a generative Large Language Model (Llama-3 8B, fine-tuned via LoRA) with a dual-expert bidirectional cross-encoder (DeBERTa-v3-large) optimized for both semantic similarity and Natural Language Inference (NLI). By aggregating these complementary models, the system effectively captures complex contextual dependencies. In the official test set, our architecture ranked 22nd out of 79 systems, achieving a Spearman Rank Correlation of 0.71 and an accuracy within the standard deviation of 82.04%.

Anthology ID:: 2026.semeval-1.115
Volume:: Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
Month:: July
Year:: 2026
Address:: San Diego, California, USA
Editors:: Ekaterina Kochmar, Debanjan Ghosh, Kai North, Mamoru Komachi
Venues:: SemEval | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 826–831
Language:
URL:: https://aclanthology.org/2026.semeval-1.115/
DOI:
Bibkey:
Cite (ACL):: Chava Laufer, Batel Turjeman, and Chaya Liebeskind. 2026. JCT 2026 - SemEval Task 5. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 826–831, San Diego, California, USA. Association for Computational Linguistics.
Cite (Informal):: JCT 2026 - SemEval Task 5 (Laufer et al., SemEval 2026)
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PDF:: https://aclanthology.org/2026.semeval-1.115.pdf

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@inproceedings{laufer-etal-2026-jct,
    title = "{JCT} 2026 - {S}em{E}val Task 5",
    author = "Laufer, Chava  and
      Turjeman, Batel  and
      Liebeskind, Chaya",
    editor = "Kochmar, Ekaterina  and
      Ghosh, Debanjan  and
      North, Kai  and
      Komachi, Mamoru",
    booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.semeval-1.115/",
    pages = "826--831",
    ISBN = "979-8-89176-414-9",
    abstract = "The system integrates a generative Large Language Model (Llama-3 8B, fine-tuned via LoRA) with a dual-expert bidirectional cross-encoder (DeBERTa-v3-large) optimized for both semantic similarity and Natural Language Inference (NLI). By aggregating these complementary models, the system effectively captures complex contextual dependencies. In the official test set, our architecture ranked 22nd out of 79 systems, achieving a Spearman Rank Correlation of 0.71 and an accuracy within the standard deviation of 82.04{\%}."
}

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    <abstract>The system integrates a generative Large Language Model (Llama-3 8B, fine-tuned via LoRA) with a dual-expert bidirectional cross-encoder (DeBERTa-v3-large) optimized for both semantic similarity and Natural Language Inference (NLI). By aggregating these complementary models, the system effectively captures complex contextual dependencies. In the official test set, our architecture ranked 22nd out of 79 systems, achieving a Spearman Rank Correlation of 0.71 and an accuracy within the standard deviation of 82.04%.</abstract>
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%0 Conference Proceedings
%T JCT 2026 - SemEval Task 5
%A Laufer, Chava
%A Turjeman, Batel
%A Liebeskind, Chaya
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F laufer-etal-2026-jct
%X The system integrates a generative Large Language Model (Llama-3 8B, fine-tuned via LoRA) with a dual-expert bidirectional cross-encoder (DeBERTa-v3-large) optimized for both semantic similarity and Natural Language Inference (NLI). By aggregating these complementary models, the system effectively captures complex contextual dependencies. In the official test set, our architecture ranked 22nd out of 79 systems, achieving a Spearman Rank Correlation of 0.71 and an accuracy within the standard deviation of 82.04%.
%U https://aclanthology.org/2026.semeval-1.115/
%P 826-831

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Markdown (Informal)

[JCT 2026 - SemEval Task 5](https://aclanthology.org/2026.semeval-1.115/) (Laufer et al., SemEval 2026)

JCT 2026 - SemEval Task 5 (Laufer et al., SemEval 2026)

ACL

Chava Laufer, Batel Turjeman, and Chaya Liebeskind. 2026. JCT 2026 - SemEval Task 5. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 826–831, San Diego, California, USA. Association for Computational Linguistics.