@inproceedings{grecu-etal-2026-argchestrators,
title = "Argchestrators at {UZH} Shared Task 2026: Efficient Argument Mining in {UN} Resolutions: A Sub-8{B} Pipeline using Agentic Debate and Heuristic Retrieval",
author = "Grecu, Bogdan Octavian and
Quaremba, Gerrit and
Black, Elizabeth and
Vrande{\v{c}}i{\'c}, Denny and
Simperl, Elena and
Cocarascu, Oana",
editor = "Elaraby, Mohamed and
Hautli-Janisz, Annette and
Romberg, Julia and
Musi, Elena and
Ruggeri, Federico and
Lawrence, John",
booktitle = "Proceedings of the 13th Workshop on Argument Mining and Reasoning",
month = jul,
year = "2026",
address = "San Diego, California, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.argmining-1.13/",
pages = "109--115",
ISBN = "979-8-89176-399-9",
abstract = "The highly formal and negotiated language of United Nations (UN) resolutions presents unique challenges for argument mining. This paper describes our system submitted to the ArgMining 2026 Shared Task: Reconstructing the Reasoning in United Nations Resolutions. Adhering to the strict constraint of utilising open-weight models with at most 8 billion parameters, we propose a hybrid, compute-efficient architecture powered by Qwen3-8B. For the preambular-operative classification, we implement a set of deterministic rules related to the specificity of UN documents, supplemented by an LLM-based multi-label classifier for thematic dimensions and a directed-graph extraction approach for argumentative relation prediction."
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<abstract>The highly formal and negotiated language of United Nations (UN) resolutions presents unique challenges for argument mining. This paper describes our system submitted to the ArgMining 2026 Shared Task: Reconstructing the Reasoning in United Nations Resolutions. Adhering to the strict constraint of utilising open-weight models with at most 8 billion parameters, we propose a hybrid, compute-efficient architecture powered by Qwen3-8B. For the preambular-operative classification, we implement a set of deterministic rules related to the specificity of UN documents, supplemented by an LLM-based multi-label classifier for thematic dimensions and a directed-graph extraction approach for argumentative relation prediction.</abstract>
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%0 Conference Proceedings
%T Argchestrators at UZH Shared Task 2026: Efficient Argument Mining in UN Resolutions: A Sub-8B Pipeline using Agentic Debate and Heuristic Retrieval
%A Grecu, Bogdan Octavian
%A Quaremba, Gerrit
%A Black, Elizabeth
%A Vrandečić, Denny
%A Simperl, Elena
%A Cocarascu, Oana
%Y Elaraby, Mohamed
%Y Hautli-Janisz, Annette
%Y Romberg, Julia
%Y Musi, Elena
%Y Ruggeri, Federico
%Y Lawrence, John
%S Proceedings of the 13th Workshop on Argument Mining and Reasoning
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-399-9
%F grecu-etal-2026-argchestrators
%X The highly formal and negotiated language of United Nations (UN) resolutions presents unique challenges for argument mining. This paper describes our system submitted to the ArgMining 2026 Shared Task: Reconstructing the Reasoning in United Nations Resolutions. Adhering to the strict constraint of utilising open-weight models with at most 8 billion parameters, we propose a hybrid, compute-efficient architecture powered by Qwen3-8B. For the preambular-operative classification, we implement a set of deterministic rules related to the specificity of UN documents, supplemented by an LLM-based multi-label classifier for thematic dimensions and a directed-graph extraction approach for argumentative relation prediction.
%U https://aclanthology.org/2026.argmining-1.13/
%P 109-115
Markdown (Informal)
[Argchestrators at UZH Shared Task 2026: Efficient Argument Mining in UN Resolutions: A Sub-8B Pipeline using Agentic Debate and Heuristic Retrieval](https://aclanthology.org/2026.argmining-1.13/) (Grecu et al., ArgMining 2026)
ACL