Research map / Graph learning / Knowledge and temporal graphs
A Graph Fusion Approach for Cross-Lingual Machine Reading Comprehension
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add syntax dependency edges to alignment edges (ablation) | GFMRC large · MLQA | F1: 77.1 -> 77.7 | Helped |
| add syntax dependency edges to alignment edges (ablation) | GFMRC large · MLQA | EM: 58.5 -> 59.0 | Helped |
| add syntax dependency edges to alignment edges (ablation) | GFMRC large · TyDiQA-GoldP | F1: 72.7 -> 73.6 | Helped |
| add syntax dependency edges to alignment edges (ablation) | GFMRC large · TyDiQA-GoldP | EM: 54.2 -> 55.4 | Helped |
| add graph pre-training on parallel data (ablation) | GFMRC large with alignment and syntax edges · MLQA | F1: 77.7 -> 78.1 | Helped |
| add graph pre-training on parallel data (ablation) | GFMRC large with alignment and syntax edges · MLQA | EM: 59.0 -> 59.4 | Helped |
| add graph pre-training on parallel data (ablation) | GFMRC large with alignment and syntax edges · TyDiQA-GoldP | F1: 73.6 -> 74.2 | Helped |
| add graph pre-training on parallel data (ablation) | GFMRC large with alignment and syntax edges · TyDiQA-GoldP | EM: 55.4 -> 56.0 | Helped |
Closest papers by meaning
- Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency Graph (AAAI 2022 · similarity 0.92)
- From Good to Best: Two-Stage Training for Cross-Lingual Machine Reading Comprehension (AAAI 2022 · similarity 0.91)
- Soft Token Alignment for Cross-Lingual Reasoning (NeurIPS 2026 · similarity 0.86)
- MCIF: Multimodal Crosslingual Instruction-Following Benchmark from Scientific Talks (ICLR 2026 · similarity 0.85)
- A Benchmark for Learning to Translate a New Language from One Grammar Book (ICLR 2024 · similarity 0.85)
- Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis (AAAI 2025 · similarity 0.85)
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