Papers with encoding strategies
Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs (2020.tacl-1)
Copied to clipboard
| Challenge: | Recent graph-to-text models generate text from graph data using global or local aggregation . global node encoding allows explicit communication between two distant nodes, but fails to capture long-range relationships. |
| Approach: | They propose to combine global and local aggregation to learn node representations . they propose to use global and locally encoding to learn contextualized node embeddings based on graph data . |
| Outcome: | The proposed models outperform state-of-the-art models on two graph-to-text datasets by 18.01 and 63.69 points. |
"Newspaper Eat" Means "Not Tasty": A Taxonomy and Benchmark for Coded Language in Real-World Chinese Online Reviews (2026.acl-long)
Copied to clipboard
| Challenge: | Current language models handle coded language poorly, with limited real-world datasets and clear taxonomies. |
| Approach: | They propose a taxonomy that captures common encoding strategies including phonetic, orthographic, and cross-lingual substitutions. |
| Outcome: | The proposed model fails to detect or understand coded language in Chinese reviews . negative reviews can expose users to social pressure, retaliation, or reduced visibility . |