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Adapter-based Selective Knowledge Distillation for Federated Multi-domain Meeting Summarization
Xiachong Feng, Xiaocheng Feng, Xiyuan Du +2
Meeting summarization has emerged as a promising technique for providing users with condensed summaries. However, existing work has focused on training models on centralized data,…
SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills
Zhangyin Feng, Yong Dai, Fan Zhang +6
Traditional multitask learning methods basically can only exploit common knowledge in task- or language-wise, which lose either cross-language or cross-task knowledge. This paper p…
A Diffusion Model for Event Skeleton Generation
Fangqi Zhu, Lin Zhang, Jun Gao +3
Event skeleton generation, aiming to induce an event schema skeleton graph with abstracted event nodes and their temporal relations from a set of event instance graphs, is a critic…
Improved Visual Story Generation with Adaptive Context Modeling
Zhangyin Feng, Yuchen Ren, Xinmiao Yu +4
Diffusion models developed on top of powerful text-to-image generation models like Stable Diffusion achieve remarkable success in visual story generation. However, the best-perform…
Towards Higher Pareto Frontier in Multilingual Machine Translation
Yichong Huang, Xiaocheng Feng, Xinwei Geng +2
Multilingual neural machine translation has witnessed remarkable progress in recent years. However, the long-tailed distribution of multilingual corpora poses a challenge of Pareto…
NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing
Tingting Wu, Xiao Ding, Minji Tang +3
Large-scale datasets in the real world inevitably involve label noise. Deep models can gradually overfit noisy labels and thus degrade model generalization. To mitigate the effects…