{
 "id": "NeoHugh/TrapQA",
 "owner": "NeoHugh",
 "name": "TrapQA",
 "downloads": 115,
 "likes": 1,
 "last_modified": "2026-10-27T22:20:43.000Z",
 "stated_licence": "cc-by-sa-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "question-answering"
 ],
 "citation": "@inproceedings{hu-etal-2026-understanding,\n    title = \"Understanding Why Language Models Hallucinate: Testing Reasoning Against Priors\",\n    author = \"Hu, Yangfan  and\n      Tong, Xuhan  and\n      Bai, Haoyue  and\n      Ding, Xi  and\n      Bharadwaj, Shashank Muralidhar  and\n      Cao, Siyang  and\n      Nowak, Robert D  and\n      Zhang, Jiawei\",\n    editor = \"Lee, Hung-Yi  and\n      Dev, Sunipa  and\n      Li, Jessy  and\n      Elliott, Desmond\",\n    booktitle = \"Findings of the {A}ssociation for {C}omputational {L}inguistics: {EMNLP} 2026\",\n    month = oct,\n    year = \"2026\",\n    address = \"Budapest, Hungary\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2026.findings-emnlp.2092/\",\n    pages = \"44555--44581\",\n    ISBN = \"979-8-89176-462-0\",\n    abstract = \"Large language models often produce hallucinated answers that violate prompt-level constraints. A key diagnostic question is whether these failures reflect missing knowledge, or whether the model has the relevant information but follows the wrong inference path. We study this phenomenon as *inference misalignment*: a mismatch between the answer supported by the prompt and the answer favored by statistically salient latent associations. We formalize this view with a latent key{--}task model, in which pretraining-frequency imbalance can cause a shortcut path to dominate the constraint-sensitive path and induce positive inference loss. The framework predicts two failure modes",
 "signal": "permissive",
 "reason": "The declared licence (cc-by-sa-4.0) is classified as share-alike.",
 "revision": "628c5f80aff4d65eaec592a68dfa4c485b31332f",
 "stated_evidence": "https://huggingface.co/datasets/NeoHugh/TrapQA/blob/628c5f80aff4d65eaec592a68dfa4c485b31332f/README.md",
 "file_evidence": "https://huggingface.co/datasets/NeoHugh/TrapQA/tree/628c5f80aff4d65eaec592a68dfa4c485b31332f",
 "card_nc": false
}