Generated data
Training sets we generated or augmented for the released models. Each row is text, target, stance
with stance in {Favor, Against, None}. Paths match what the configs and training scripts expect,
so run them with this folder as the data root.
| File | Rows | How it was made | Used by |
|---|---|---|---|
track2/train_aug.csv |
8,056 | Track-2 train plus LLM paraphrases; a source column marks original (2,714) or paraphrase (5,342) |
encoder t2_marbert_aug, via configs/track2_aug.yaml |
synth/t1_train_style.csv |
3,902 | Track-1 train plus style-grounded generated shots | LoRA allam_style |
external/pool_real_all.csv |
4,449 | pooled real-target shots (Women Empowerment, Covid, Digital) | LoRA allam_real |
The official Mawqif-v2 splits belong to the organizers and are not redistributed here. Get them from the shared task at https://stanceeval.github.io/. Everything above is derived from those splits and can be regenerated:
python -m src.gen_synth --help # style and target-matched shot pools
python -m src.augment --help # paraphrase augmentation