All datasets / cswbyu
cswbyu/CHILLGuardTrain-Subset-15K
The declared licence (cc-by-nc-4.0) is classified as having use restrictions.
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Citation text from the card
@inproceedings{yu-etal-2026-chillguard,
title = "{CHILLG}uard: Towards Fine-Grained {C}hinese {LLM} Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment",
author = "Yu, Wenbo and
Wang, Bohua and
Fang, Hao and
Gao, Kuofeng and
Zeng, Jingru and
Yang, Xiaochen and
Zhang, Tianyi and
Ma, Xiaoxiao and
Kong, Jiawei and
Wu, Hao and
Chen, Bin and
Xia, Shu-Tao and
Zhang, Min",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {EMNLP} 2026",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.findings-emnlp.1721/",
doi = "10.18653/2026.findings-emnlp.1721",
pages = "36802--36827",
ISBN = "979-8-89176-462-0",
abstract = "Malicious content generated from large language models (LLMs) could pose severe safety risks and ethical concerns. While existing LLM safety guardrails excel in English or multilingual settings, they lack adaptation to Chinese-specific regulatory policies, cultural context, and linguistic nuances, failing to support fine-grained risk classification for diverse dep
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dataset_licence({ "id": "cswbyu/CHILLGuardTrain-Subset-15K" })
signal: "restrictive"
stated_licence: "cc-by-nc-4.0"
sources: 0