Papers by Roshanak Mirzaee

3 papers
Transfer Learning with Synthetic Corpora for Spatial Role Labeling and Reasoning (2022.emnlp-main)

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Challenge: Existing datasets on spatial language processing are either synthetic or at small scale.
Approach: They propose a dataset for transfer learning on spatial question answering and spatial role labeling that includes a larger variety of spatial relation types and spatial expressions.
Outcome: The proposed dataset can be used to evaluate spatial language processing models in real-world situations.
SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning (2021.naacl-main)

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Challenge: Existing studies have focused on the spatial reasoning capabilities of modern language models (LMs) however, there has been limited research into the spatial thinking capabilities of LMs.
Approach: They propose a question-answering (QA) benchmark for spatial reasoning on natural language text which contains more realistic spatial phenomena not covered by prior work.
Outcome: The proposed method significantly improves LMs' ability on spatial understanding, which in turn helps solve two external datasets, bAbI, and boolQ.
Disentangling Extraction and Reasoning in Multi-hop Spatial Reasoning (2023.findings-emnlp)

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Challenge: Recent studies highlight the struggles even large language models encounter when it comes to performing spatial reasoning over text.
Approach: They propose to disentangle spatial reasoning over text and compare them to state-of-the-art models with no explicit design for these parts.
Outcome: The proposed models show that they can perform spatial reasoning over text and can generalize within real data domains.

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