Character-level bi-LSTM seq2seq
Reported on 2 benchmarks across 1 task · 1 paper · 2 SOTA
Note: results are matched by exact model name. Different papers may use the same name for different model variants.
Natural Language Processing2 results
- F1· 2018-10-30SOTA83.3best: 88.3 (Bi-LSTM seq2seq: BERT + characters in 1 encoder)
- F1· 2018-10-30SOTA84.9best: 89.3 (Bi-LSTM seq2seq: BERT + characters in 1 encoder)