Evaluating Bias in Chinese Large Language Models across Tasks and Registers: Task Operationalization Effects and Irony Classification Risks
cs.CL, cs.CY
Submitted: 2026-10-10
Updated: 2026-10-10
Comments: 11 pages, 3 figures
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Alignment faking in large language models
- Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
- Evaluating and Mitigating Discrimination in Language Model Decisions
- Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
- Irony in Emojis: A Comparative Study of Human and LLM Interpretation
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