mlsanityData to 14 Oct 2026

Nowruz at SemEval-2022 Task 7: Tackling Cloze Tests with Transformers and Ordinal Regression

arXiv 2204.00556 ↗First posted 1 Apr 2022cs.CL cs.AIcited by 1

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Abstract (arXiv)

This paper outlines the system using which team Nowruz participated in SemEval 2022 Task 7 Identifying Plausible Clarifications of Implicit and Underspecified Phrases for both subtasks A and B. Using a pre-trained transformer as a backbone, the model targeted the task of multi-task classification and ranking in the context of finding the best fillers for a cloze task related to instructional texts on the website Wikihow. The system employed a combination of two ordinal regression components to tackle this task in a multi-task learning scenario. According to the official leaderboard of the shared task, this system was ranked 5th in the ranking and 7th in the classification subtasks out of 21 participating teams. With additional experiments, the models have since been further optimised.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 23 references that are in the map. First posted on arXiv 1 Apr 2022.

Builds on

11 of 23 references.

References · 11

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Citing papers per year: 2025: 1.

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  1. 2025InstructNet: A Novel Approach for Multi-Label Instruction Classification through Advanced Deep Learningcited by 2