Papers by Mingtao Dong
Does Your Model Classify Entities Reasonably? Diagnosing and Mitigating Spurious Correlations in Entity Typing (2022.emnlp-main)
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| Challenge: | Existing entity typing models are subject to spurious correlations due to shortcuts and biased training. |
| Approach: | They propose a method to augment existing model biases by combining spurious correlations with debiasedcounterparts to improve generalization. |
| Outcome: | The proposed method improves generalization of different entity typing models on the original and debiased test sets. |
Dense Retrieval as Indirect Supervision for Large-space Decision Making (2023.findings-emnlp)
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| Challenge: | Dense Decision Retrieval (DDR) is a learning-to-retrieve task for discriminative natural language understanding (NLU) tasks with large label spaces. |
| Approach: | They propose a novel approach to learning large-space discriminative NLU tasks as a learning-to-retrieve task by adopting a dual-encoder architecture that learns to predict by retrieving from a decision thesaurus. |
| Outcome: | The proposed approach outperforms baselines greatly on multi-label classification tasks, 1.17% in F1 score ultra-fine entity typing, and 1.26% in accuracy on three few-shot intent classification tasks on average. |