Research map / Label-efficient and robust learning / Domain adaptation and generalization
A Representation Learning Framework for Multi-Source Transfer Parsing
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add unified multilingual lexical features (MULTI-PROJ) (ablation) | MULTI-DELEX · Google UDT v2.0 AVG | LAS: 62.79 -> 69.32 | Helped |
| add unified multilingual lexical features (MULTI-SG) (ablation) | MULTI-DELEX · Google UDT v2.0 AVG | LAS: 62.79 -> 67.97 | Helped |
| use multilingual robust projection instead of multilingual skip-gram (ablation) | MULTI-SG · Google UDT v2.0 AVG | LAS: 67.97 -> 69.32 | Helped |
| use multi-source treebanks instead of English-only source (delexicalized) | Guo15 · Google UDT v2.0 ES | LAS: 62.28 -> 64.68 | Helped |
| use multi-source treebanks instead of English-only source (delexicalized) | Guo15 · Google UDT v2.0 DE | LAS: 51.54 -> 49.82 | Hurt |
| fine-tune on 50 target-language sentences | MULTI-PROJ · Google UDT v2.0 AVG | LAS: +4.41 | Helped |
| fine-tune on 50 target-language sentences | MULTI-DELEX · Google UDT v2.0 ES | UAS: 73.46(−2.08) | Hurt |
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