Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval

Understand

Dual-Encoders is a promising mechanism for answer retrieval in question answering (QA) systems.

• Currently most conventional Dual-Encoders learn the semantic representations of questions and answers merely through matching score.
• Researchers proposed to introduce the QA interaction features in scoring function but at the cost of low efficiency in inference stage.
• To keep independent encoding of questions and answers during inference stage, variational auto-encoder is further introduced to reconstruct answers (questions) from question (answer) embeddings as an auxiliary task to enhance QA interaction in representation learning in training stage.