mlsanityData to 7 Oct 2026

mdok-style at SemEval-2026 Task 10: Finetuning LLMs for Conspiracy Detection

arXiv 2605.02712 ↗First posted 4 May 2026cs.CL cs.AIcited by 0

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Abstract (arXiv)

SemEval-2026 Task 10 is focused on conspiracy detection. Specifically, the goal is to detect whether a Reddit comment expresses a conspiracy belief. Our submitted mdok-style system utilizes data augmentation and self-training (to cope with a rather small amount of training data) to finetune the Qwen3-32B model for a binary text-classification task. The submitted system is very competitive, ranking in the 85th percentile (8th out of 52 submissions). The results shown that our approach, which originated in machine-generated text detection, can be used for conspiracy detection as well.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 12 references that are in the map. First posted on arXiv 4 May 2026.

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3 of 12 references.

References · 3

  1. 2023IMGTB: A Framework for Machine-Generated Text Detection Benchmarkingcited by 12
  2. 2025Increasing the Robustness of the Fine-tuned Multilingual Machine-Generated Text Detectorscited by 8
  3. 2025mdok of KInIT: Robustly Fine-tuned LLM for Binary and Multiclass AI-Generated Text Detectioncited by 6

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