6 papers
Culture-Aware Machine Translation in Large Language Models: Benchmarking and Investigation
Zekun Yuan, Yangfan Ye, Xiaocheng Feng +5
Large language models (LLMs) have achieved strong performance in general machine translation, yet their ability in culture-aware scenarios remains poorly understood. To bridge this…
CAI: Caption-Sensitive Attention Intervention for Mitigating Object Hallucination in Large Vision-Language Models
Qiming Li, Zekai Ye, Xiaocheng Feng +8
Although Large Vision-Language Models (LVLMs) have demonstrated powerful capabilities in interpreting visual information, they frequently produce content that deviates from visual…
CLAIM: Mitigating Multilingual Object Hallucination in Large Vision-Language Models with Cross-Lingual Attention Intervention
Zekai Ye, Qiming Li, Xiaocheng Feng +10
Large Vision-Language Models (LVLMs) have demonstrated impressive multimodal abilities but remain prone to multilingual object hallucination, with a higher likelihood of generating…
One for All: Update Parameterized Knowledge Across Multiple Models
Weitao Ma, Xiyuan Du, Xiaocheng Feng +8
Large language models (LLMs) encode vast world knowledge but struggle to stay up-to-date, often leading to errors and hallucinations. Knowledge editing offers an efficient alternat…
Enhancing Non-English Capabilities of English-Centric Large Language Models through Deep Supervision Fine-Tuning
Wenshuai Huo, Xiaocheng Feng, Yichong Huang +9
Large language models (LLMs) have demonstrated significant progress in multilingual language understanding and generation. However, due to the imbalance in training data, their cap…
Ensuring Consistency for In-Image Translation
Chengpeng Fu, Xiaocheng Feng, Yichong Huang +9
The in-image machine translation task involves translating text embedded within images, with the translated results presented in image format. While this task has numerous applicat…