11 papers
Reason Analogically via Cross-domain Prior Knowledge: An Empirical Study of Cross-domain Knowledge Transfer for In-Context Learning
Le Liu, Zhiming Li, Jianzhi Yan +7
Despite its success, existing in-context learning (ICL) relies on in-domain expert demonstrations, limiting its applicability when expert annotations are scarce. We posit that diff…
Towards Effective In-context Cross-domain Knowledge Transfer via Domain-invariant-neurons-based Retrieval
Jianzhi Yan, Zhiming Li, Le Liu +6
Large language models (LLMs) have made notable progress in logical reasoning, yet still fall short of human-level performance. Current boosting strategies rely on expert-crafted in…
Mitigating Translationese Bias in Multilingual LLM-as-a-Judge via Disentangled Information Bottleneck
Hongbin Zhang, Kehai Chen, Xuefen Bai +4
Large language models (LLMs) have become a standard for multilingual evaluation, yet they exhibit a severe systematic translationese bias. In this paper, translationese bias is cha…
Scalable Multilingual Multimodal Machine Translation with Speech-Text Fusion
Yexing Du, Youcheng Pan, Zekun Wang +7
Multimodal Large Language Models (MLLMs) have achieved notable success in enhancing translation performance by integrating multimodal information. However, existing research primar…
MCGA: A Multi-task Classical Chinese Literary Genre Audio Corpus
Yexing Du, Kaiyuan Liu, Bihe Zhang +9
With the rapid advancement of Multimodal Large Language Models (MLLMs), their potential has gained significant attention in Chinese Classical Studies (CCS). While existing research…
MCAT: Scaling Many-to-Many Speech-to-Text Translation with MLLMs to 70 Languages
Yexing Du, Kaiyuan Liu, Youcheng Pan +7
Multimodal Large Language Models (MLLMs) have achieved great success in Speech-to-Text Translation (S2TT) tasks. However, current research is constrained by two key challenges: lan…