Dominik Macko
We lifted 2 functions out of this paper's own repositories and ran 2 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| kinit-sk/mdok-style-psycomark2026 | canonical | 2 of 2 |
| Function | Status | Where it lives |
|---|---|---|
| anonymize | Ran | kinit-sk/mdok-style-psycomark2026/mdok-style.py pointer only (licence: GPL-3.0) · get_code("7c52f16ec20ace78") |
| load_and_filter_data | Ran | kinit-sk/mdok-style-psycomark2026/mdok-style.py pointer only (licence: GPL-3.0) · get_code("2c36dea83d855974") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
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.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2605.02712")
get_code_for_paper("2605.02712")
have("2605.02712")
Connect an agent — have() is free.