論文：Learning Matching Models with Weak Supervision for Response Selection in Retrieval-based Chatbots
論文連接：https://arxiv.org/abs/1805.02333app 本文提出了一種用seq2seq給每一個（context， response）pair打分，並把這個分數做爲「soft」 margin 用linear svm loss來進行訓練的方法，有針對性地解決了當前訓練檢索式對話系統的matching model，在訓練時sample negative responses的時候
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相關文章
- 1. 檢索式多輪對話系統論文：Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network 閱讀筆記
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