• 专利标题: LEARNING LANGUAGE REPRESENTATION WITH LOGICAL INDUCTIVE BIAS
  • 申请号: US18077723
    申请日: 2022-12-08
  • 公开(公告)号: US20240193399A1
    公开(公告)日: 2024-06-13
  • 发明人: Jianshu CHEN
  • 申请人: TENCENT AMERICA LLC
  • 申请人地址: US CA Palo Alto
  • 专利权人: TENCENT AMERICA LLC
  • 当前专利权人: TENCENT AMERICA LLC
  • 当前专利权人地址: US CA Palo Alto
  • 主分类号: G06N3/04
  • IPC分类号: G06N3/04
LEARNING LANGUAGE REPRESENTATION WITH LOGICAL INDUCTIVE BIAS
摘要:
A method including receiving input comprising natural language texts; pre-training a First-Order Logic Network (FOLNet) neural network model on unlabeled texts included in the natural language texts, the FOLNet neural network model comprising of a plurality of layers; processing the input through the plurality of layers of the FOLNet neural network model; encoding a logical inductive bias using the FOLNet neural network model; outputting one or more tensors based on the logical inductive bias; and predicting an outcome using the one or more tensors.
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