CLaC at SemEval-2026 Task 6: Response Clarity Detection in Political Discourse
In this paper, we present our system for SemEval-2026 Task 6 (CLARITY) on response clarity and evasion detection in question-answer pairs from U.S. presidential interviews, comparing fine-tuned encoders with prompt-based LLMs. Our LLM ensemble achieves 80 macro-F1 on the 3-class Task 1 (9th/41) and 59 on the 9-class Task 2 (3rd/33). Across 8 transformer encoders optimized through a four-stage pipeline, partial encoder layer unfreezing outperforms full fine-tuning by a wide margin. Combining English and multilingual encoders further improves ensemble performance over either family alone, despite multilingual models being individually weaker. Prompt-based LLMs, without any task-specific par...
| Authors | Nawar Turk, Lucas Miquet-Westphal, Leila Kosseim |
|---|---|
| Primary category | cs.CL |
| Published | 4 May 2026 |
| Last updated at source | 4 May 2026 |
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