An LLM ensemble reached 80 macro-F1 on 3-class clarity detection and 59 on 9-class evasion detection, with partial layer unfreezing and multilingual ensembles improving encoder results while enriched context helped only LLMs.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A multi-head RoBERTa model with overlapping chunking and max-pooling achieves Macro-F1 of 0.80 on 3-way clarity classification and 0.51 on 9-way evasion strategy detection, ranking 11th in both subtasks of SemEval-2026 Task 6.
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CLaC at SemEval-2026 Task 6: Response Clarity Detection in Political Discourse
An LLM ensemble reached 80 macro-F1 on 3-class clarity detection and 59 on 9-class evasion detection, with partial layer unfreezing and multilingual ensembles improving encoder results while enriched context helped only LLMs.
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SG-UniBuc-NLP at SemEval-2026 Task 6: Multi-Head RoBERTa with Chunking for Long-Context Evasion Detection
A multi-head RoBERTa model with overlapping chunking and max-pooling achieves Macro-F1 of 0.80 on 3-way clarity classification and 0.51 on 9-way evasion strategy detection, ranking 11th in both subtasks of SemEval-2026 Task 6.