Papers with relational reasoning tasks

3 papers
Working Memory Networks: Augmenting Memory Networks with a Relational Reasoning Module (P18-1)

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Challenge: Recent advances in deep neural networks have enabled complex reasoning tasks.
Approach: They propose a MemNN architecture with a working memory storage and reasoning module that retains relational reasoning abilities of relation networks while reducing computational complexity.
Outcome: The proposed model retains the relational reasoning abilities of the RN while reducing its computational complexity from quadratic to linear.
UniEvent: Unified Generative Model with Multi-Dimensional Prefix for Zero-Shot Event-Relational Reasoning (2023.acl-long)

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Challenge: Reasoning about events and their relations is an indispensable ability to fulfill various event-centric or common-sense reasoning tasks.
Approach: They propose a multi-task learning framework that organizes event relational reasoning tasks into a coordinate system with multiple axes, representing inter-event relations and reasoning formulations.
Outcome: The proposed framework achieves state-of-the-art or competitive performance on zero-shot and supervised reasoning tasks.
Document-Level Relation Extraction with Global Relations and Entity Pair Reasoning (2025.findings-acl)

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Challenge: Existing document-level relation extraction models focus on individual entity pairs, limiting their ability to handle complex reasoning tasks.
Approach: They propose a document-level relation extraction framework based on global relations and entity pair reasoning that captures fine-grained interactions between entity pairs.
Outcome: The proposed framework outperforms existing models on widely-used datasets.

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