MTGER: Multi-view Temporal Graph Enhanced Temporal Reasoning over Time-Involved Document
On the map: LLM reasoning → Knowledge- and tool-augmented reasoning
Abstract (arXiv)
The facts and time in the document are intricately intertwined, making temporal reasoning over documents challenging. Previous work models time implicitly, making it difficult to handle such complex relationships. To address this issue, we propose MTGER, a novel Multi-view Temporal Graph Enhanced Temporal Reasoning framework for temporal reasoning over time-involved documents. Concretely, MTGER explicitly models the temporal relationships among facts by multi-view temporal graphs. On the one hand, the heterogeneous temporal graphs explicitly model the temporal and discourse relationships among facts; on the other hand, the multi-view mechanism captures both time-focused and fact-focused information, allowing the two views to complement each other through adaptive fusion. To further improve the implicit reasoning capability of the model, we design a self-supervised time-comparing objective. Extensive experimental results demonstrate the effectiveness of our method on the TimeQA and SituatedQA datasets. Furthermore, MTGER gives more consistent answers under question perturbations.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 3 of its 45 references that are in the map. First posted on arXiv 8 Nov 2023.
Builds on
3 of 45 references.
References · 3
- 2020Longformer: The Long-Document Transformercited by 3,362
- 2023Multimodal Chain-of-Thought Reasoning in Language Modelscited by 740
- 2019Relational Graph Attention Networkscited by 81
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.
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- 2023Fusing Temporal Graphs into Transformers for Time-Sensitive Question Answering
- 2023Once Upon a textitTime in textitGraph: Relative-Time Pretraining for Complex Temporal Reasoning
- 2026SCoP: Structured Constraint Parsing for Evidence-Space Control in Temporal Knowledge Graph Question Answering
- 2025Towards Foundation Model on Temporal Knowledge Graph Reasoning
- 2024Deja vu: Contrastive Historical Modeling with Prefix-tuning for Temporal Knowledge Graph Reasoning
- 2024Large Language Models Can Learn Temporal Reasoning