Papers by Ada Tur
Comparing Approaches to Language Understanding for Human-Robot Dialogue: An Error Taxonomy and Analysis (2022.lrec-1)
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| Challenge: | Existing approaches to language understanding for human-robot interaction are limited by domain-specific grammars and domain-level inputs. |
| Approach: | They compare a relevance-based classifier with a GPT-2 model and compare their results . they find that the relevance- and GPT-based models make different errors . |
| Outcome: | The proposed model outperforms the existing model with 2000 examples as training data. |
Language Models Largely Exhibit Human-like Constituent Ordering Preferences (2025.naacl-long)
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| Challenge: | English sentences are typically inflexible vis-à-vis word order, but constituents show far more variability in ordering. |
| Approach: | They compare LLMs with four types of constituent movement to evaluate their performance on heavy NP shift, particle movement, dative alternation, and multiple PPs. |
| Outcome: | The proposed model performs well on four types of constituent movement: heavy NP shift, particle movement, dative alternation, and multiple PPs. |