The widespread dissemination of toxic online posts is increasingly damaging to society. However, research on detecting toxic language in Chinese has lagged significantly. Existing datasets lack fine-grained annotation of toxic types and expressions, and ignore the samples with indirect toxicity. In addition, it is crucial to introduce lexical knowledge to detect the toxicity of posts, which has been a challenge for researchers. In this paper, we facilitate the fine-grained detection of Chinese toxic language. First, we built Monitor Toxic Frame, a hierarchical taxonomy to analyze toxic types and expressions. Then, a fine-grained dataset ToxiCN is presented, including both direct and indirect toxic samples. We also build an insult lexicon containing implicit profanity and propose Toxic Knowledge Enhancement (TKE) as a benchmark, incorporating the lexical feature to detect toxic language. In the experimental stage, we demonstrate the effectiveness of TKE. After that, a systematic quantitative and qualitative analysis of the findings is given.
Distinguishing Right from Wrong in Debates: Attribution Analysis of Chinese Harmful Memes
Key Laboratory of Social Computing and Cognitive Intelligence, Dalian University of Technology（社会计算与认知智能重点实验室，大连理工大学）；Singapore University of Technology and Design（新加坡科技设计大学）；Data Intelligence Lab, Department of Computer Science, City University of Hong Kong（数据智能实验室，香港城市大学计算机科学系）
ToxiTrace: Gradient-Aligned Training for Explainable Chinese Toxicity Detection
School of Data Science and Engineering, East China Normal University（数据科学与工程学院，东华大学）；School of International Chinese Studies, East China Normal University（国际中文学院，东华大学）
ChineseWebText 2.0: Large-Scale High-quality Chinese Web Text with Multi-dimensional and fine-grained information
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）
T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Beihang University（北航）；Harbin Institute of Technology（哈尔滨工业大学）；Chinese University of Hong Kong (Shenzhen)（香港中文大学（深圳））；The University of Hong Kong（香港大学）
New Terms, New Toxicity: Consensus-based Chinese Neologism Toxicity Detection via Search-Augmented LLMs
Tsinghua University（清华大学）；ICT, CAS（中国科学院计算技术研究所）；National Computer Network Emergency Response Technical Team Coordination Center of China（国家计算机网络应急技术处理协调中心）；IIE, CAS（中国科学院工程热物理研究所）；School of Cyber Security, UCAS（中国科学院大学网络空间安全学院）；JCSS, Tsinghua University（清华大学软件学院）；Science City (Guangzhou) Digital Technology Group Co., Ltd.（广州科学城数字科技集团有限公司）
Towards Comprehensive Detection of Chinese Harmful Memes
School of Computer Science and Technology（计算机科学与技术学院）；School of Foreign Languages（外国语学院）；Key Laboratory of Social Computing and Cognitive Intelligence（社会计算与认知智能重点实验室）；Dalian University of Technology（大连理工大学）
Oraichain Labs（Oraichain实验室）；VinAI Research（VinAI研究院）；Florida International University（佛罗里达国际大学）；Hanoi University of Science and Technology（河内科技大学）；University of Oregon（俄勒冈大学）
EHR-Bench: A Chinese Multi-Task Benchmark for Recruitment AI
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Alibaba Group（阿里巴巴集团）；Guangzhou University（广州大学）；University of Electronic Science and Technology of China（电子科技大学）
Rethinking Toxicity Evaluation in Large Language Models: A Multi-Label Perspective
School of Computer Science and Engineering, Southeast University（东南大学计算机科学与工程学院）；RIKEN Center for Advanced Intelligence Project (AIP)（RIKEN先进人工智能项目中心）；School of Computer Science and Technology, Qilu University of Technology（齐鲁大学计算机科学与技术学院）；The University of Tokyo（东京大学）
Lost in Pronunciation: Detecting Chinese Offensive Language Disguised by Phonetic Cloaking Replacement
School of Computer Science, The University of Sydney（悉尼大学计算机科学学院）；Business School, The Hong Kong University of Science and Technology（香港科技大学商学院）；Australian AI Institute, University of Technology Sydney（悉尼科技大学澳大利亚人工智能研究所）；School of Advanced Technology, Xi’an Jiaotong-Liverpool University（西安交通大学利物浦大学先进技术学院）
CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Models
College of Intelligence and Computing, Tianjin University（天津大学智能与计算学部）；School of Computer and Artificial Intelligence, Zhengzhou University（郑州大学计算机与人工智能学院）
CANDY: Benchmarking LLMs' Limitations and Assistive Potential in Chinese Misinformation Fact-Checking
School of Cyber Science and Engineering, Sichuan University, China（四川大学网络科学与工程学院）；College of Computer Science, Sichuan University, China（四川大学计算机学院）；Institute of Data Science, National University of Singapore, Singapore（新加坡国立大学数据科学研究所）
Multilingual and Explainable Text Detoxification with Parallel Corpora
Technical University of Munich（慕尼黑工业大学）；Universidade de Santiago de Compostela（圣地亚哥-德孔波斯特拉大学）；Shenkar College（申卡尔学院）；University of Hamburg（汉堡大学）；Bahir Dar University（巴达尔大学）；IIT Kharagpur（印度理工学院克勒格布尔分校）；Skoltech（斯科尔科沃科技学院）；AIRI（人工智能研究所）；University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）；University of Sharjah（沙迦大学）
CHILLGuard: Towards Fine-Grained Chinese LLM Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment
Tsinghua University（清华大学）；Beijing Normal University（北京师范大学）；South China University of Technology（华南理工大学）；Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））；Shenzhen ShenNong Information Technology Co., Ltd.（深圳神农信息技术有限公司）
SC-Taxo: Hierarchical Taxonomy Generation under Semantic Consistency Constraints using Large Language Models
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；University of Science and Technology Beijing（北京科技大学）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）
Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition
School of Computer Science, Fudan University（复旦大学计算机科学学院）；Honor Device Co., Ltd（荣誉设备有限公司）；Institute of Modern Languages and Linguistics, Fudan University（复旦大学现代语言与语言学研究所）；Pengcheng Laboratory（鹏城实验室）；Research Institute of Intelligent Complex Systems, Fudan University（复旦大学智能复杂系统研究院）；Shanghai Key Laboratory of Intelligent Information Processing（上海智能信息处理重点实验室）
Benchmarking Chinese Medical LLMs: A Medbench-based Analysis of Performance Gaps and Hierarchical Optimization Strategies
Shanghai Institute of Infectious Disease and Biosecurity, Fudan University（复旦大学附属上海市感染与生物安全研究院）；Shanghai Health Development Research Center(Shanghai Medical Information Center)（上海卫生发展研究中心（上海市医学信息中心））；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）
