Papers by Nanjiang Jiang
Do You Know That Florence Is Packed with Visitors? Evaluating State-of-the-art Models of Speaker Commitment (P19-1)
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| Challenge: | Existing models for speaker commitment fail to generalize to diverse linguistic constructions, highlighting directions for improvement. |
| Approach: | They evaluate two state-of-the-art speaker commitment models on the CommitmentBank . they analyze linguistic correlates of model error on a naturalistic dataset . |
| Outcome: | The proposed models perform well on some classes but fail to generalize to diverse linguistic constructions. |
Graph-Based Decoding for Task Oriented Semantic Parsing (2021.findings-emnlp)
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| Challenge: | Existing paradigms for semantic parsing are sequence-to-sequence and AMR parsers. |
| Approach: | They propose to formulate parsing as a sequence-to-sequence task using graph-based decoding techniques developed for syntactic parsers. |
| Outcome: | The proposed approach is competitive with sequence decoders on the standard setting and offers significant improvements in data efficiency and data availability. |
He Thinks He Knows Better than the Doctors: BERT for Event Factuality Fails on Pragmatics (2021.tacl-1)
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| Challenge: | Existing models for factuality prediction are lacking for English . Traditionally, event factualism is triggered by fixed properties of lexical items . |
| Approach: | They propose a model that exploits common surface patterns that correlate with factuality labels. |
| Outcome: | The proposed model achieves the best performance on four factuality datasets. |
Evaluating BERT for natural language inference: A case study on the CommitmentBank (D19-1)
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| Challenge: | Natural language inference datasets can identify premise-hypothesis relationship without observing premise . recasting of the CommitmentBank for NLI creates hypotheses that stand in entailment/contradiction/neutral relationship with premise. |
| Approach: | They propose to recast the CommitmentBank for NLI to stand in certain relationships with the premise . hypotheses are complements of clause-embedding verbs in each premise, rethinking the CommittedBank . |
| Outcome: | The proposed model performs well on the CommitmentBank with 85% F1 . however, the model does not capture the full complexity of pragmatic reasoning, authors say . |