Papers with diagnostic method

3 papers
To What Extent Do Natural Language Understanding Datasets Correlate to Logical Reasoning? A Method for Diagnosing Logical Reasoning. (2022.coling-1)

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Challenge: Reasoning and knowledge-related skills are considered as fundamental skills for natural language understanding (NLU) tasks.
Approach: They propose a method to diagnose correlations between an NLU dataset and a specific skill.
Outcome: The proposed method is able to diagnose correlations between dataset and logical reasoning skill on 8 MRC and 3 NLI datasets.
Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI (2021.emnlp-main)

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Challenge: Existing studies have focused on diagnosing LMs' reasoning abilities in natural language understanding tasks.
Approach: They propose a diagnostic method for first-order logic reasoning with a proposed benchmark, LogicNLI.
Outcome: The proposed method disentangles the target FOL reasoning from commonsense inference and can be used to diagnose LMs from four perspectives: accuracy, robustness, generalization, and interpretability.
Vision-and-Language or Vision-for-Language? On Cross-Modal Influence in Multimodal Transformers (2021.emnlp-main)

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Challenge: Pretrained vision-and-language BERTs aim to learn representations that combine information from both modalities.
Approach: They propose a diagnostic method based on cross-modal input ablation to assess the extent to which pretrained models integrate cross-module information.
Outcome: The proposed method evaluates the model's performance on the other modality based on inputs from one or both modality.

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