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cs.SD2024
When Vision Models Meet Parameter Efficient Look-Aside Adapters Without Large-Scale Audio Pretraining
Juan Yeo, Jinkwan Jang, Kyubyung Chae +2
Recent studies show that pretrained vision models can boost performance in audio downstream tasks. To enhance the performance further, an additional pretraining stage with large sc…
cs.CL2024
Model-based Preference Optimization in Abstractive Summarization without Human Feedback
Jaepill Choi, Kyubyung Chae, Jiwoo Song +2
In abstractive summarization, the challenge of producing concise and accurate summaries arises from the vast amount of information contained in the source document. Consequently, a…
cs.CL2024★ 3 cited
Mitigating Hallucination in Abstractive Summarization with Domain-Conditional Mutual Information
Kyubyung Chae, Jaepill Choi, Yohan Jo +1
A primary challenge in abstractive summarization is hallucination -- the phenomenon where a model generates plausible text that is absent in the source text. We hypothesize that th…