@inproceedings{huang-etal-2023-ensemble,
    title = "Ensemble Method via Ranking Model for Conversational Modeling with Subjective Knowledge",
    author = "Huang, Xin  and
      Min Tan, Kye  and
      Duan, Richeng  and
      Zou, Bowei",
    editor = "Chen, Yun-Nung  and
      Crook, Paul  and
      Galley, Michel  and
      Ghazarian, Sarik  and
      Gunasekara, Chulaka  and
      Gupta, Raghav  and
      Hedayatnia, Behnam  and
      Kottur, Satwik  and
      Moon, Seungwhan  and
      Zhang, Chen",
    booktitle = "Proceedings of the Eleventh Dialog System Technology Challenge",
    month = sep,
    year = "2023",
    address = "Prague, Czech Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2023.dstc-1.20/",
    pages = "177--184",
    abstract = "This paper describes our submission to the fifth track of the 11th Dialog System Technology Challenge (DSTC-11), which focuses on ``Task-oriented Conversational Modeling with Subjective Knowledge''. We focus on response generation and leverage a ranking strategy to ensemble individual models of BART, Long-T5, and a fine-tuned large language model based on LLaMA. The strategy is supplemented by other techniques like low rank adaptation to maintain efficient utilization of these large models while still achieving optimal performance. The experiments show that the ensemble method outperforms individual models and the baseline method. Our model was ranked 1st place in ROUGE{\_}1, 2nd place in ROUGE{\_}L score and 4th place in human evaluation among a total of 14 participating teams."
}