3 accepted papers
Recently, the Mixture of Expert (MoE) architecture, such as LR-MoE, is often used to alleviate the impact of language confusion on the multilingual ASR (MASR) task. However, it still faces language confusion issues, especially in mismatched domain scenarios. In this paper, we decouple language confu…
In recent years, while the performance of speech-image retrieval has improved significantly, it still lags behind that of image-text retrieval. Leveraging the text modality to enhance speech-image retrieval remains a promising research direction. In this paper, we propose to leverage text supervisio…
Large language models (LLMs) demonstrate significant generative capabilities but often face ethical alignment and robustness challenges. Conventional alignment methods rely on extensive human-annotated data and require retraining, leading to high computational costs and resource demands. Therefore,…