Papers by Chengkun Yang
SafeMT: Multi-turn Safety for Multimodal Language Models (2026.acl-long)
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Han Zhu, Juntao Dai, Jiaming Ji, Haoran Li, Chengkun Cai, Pengcheng Wen, Chi-Min Chan, Boyuan Chen, Yaodong Yang, Sirui Han, Yike Guo
| Challenge: | Multi-turn dialogues pose a greater risk than single prompts, but existing safety benchmarks do not account for this situation. |
| Approach: | They propose a benchmark that features dialogues of varying lengths generated from harmful queries accompanied by images. |
| Outcome: | The proposed model reduces multi-turn Attack Success Rate (ASR) compared to existing guard models. |
A Robust Dual-debiasing VQA Model based on Counterfactual Causal Effect (2024.findings-emnlp)
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| Challenge: | Existing VQA models suffer from language bias that indicates a spurious correlation between textual questions and answers. |
| Approach: | They propose a model agnostic dual-debiasing framework that models two types of language bias by separate branches under counterfactual inference framework. |
| Outcome: | The proposed framework significantly reduces language bias and achieves state-of-the-art performance on the benchmark datasets. |