Papers with candidate encoder

2 papers
Bring Invariant to Variant: A Contrastive Prompt-based Framework for Temporal Knowledge Graph Forecasting (2024.lrec-main)

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Challenge: Existing methods for temporal knowledge graph forecasting are insufficient structural contexts to learn effective representations.
Approach: They propose a Contrastive Prompt-based framework with Entity background information for TKG forecasting that brings time-invariant entity background information to time-variant structural information.
Outcome: The proposed framework is effective and stays competitive in inference with limited structural information.
UniRetriever: Multi-task Candidates Selection for Various Context-Adaptive Conversational Retrieval (2024.lrec-main)

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Challenge: Existing methods for retrieving information from a large corpus of data are sub-optimal and low efficiency.
Approach: They propose a multi-task framework that functions as a universal retriever for three dominant retrieval tasks during the conversation.
Outcome: The proposed framework can perform persona selection, knowledge selection, and response selection tasks simultaneously.

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