4 citations · 6 across the 4 of their papers we have counts for
5 papers
An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Fatemeh Shiri, Xiao-Yu Guo, Mona Golestan Far +3
Large Multimodal Models (LMMs) have achieved strong performance across a range of vision and language tasks. However, their spatial reasoning capabilities are under-investigated. I…
Complex Reading Comprehension Through Question Decomposition
Xiao-Yu Guo, Yuan-Fang Li, Gholamreza Haffari
Multi-hop reading comprehension requires not only the ability to reason over raw text but also the ability to combine multiple evidence. We propose a novel learning approach that h…
Teaching Neural Module Networks to Do Arithmetic
Jiayi Chen, Xiao-Yu Guo, Yuan-Fang Li +1
Answering complex questions that require multi-step multi-type reasoning over raw text is challenging, especially when conducting numerical reasoning. Neural Module Networks(NMNs),…
Improving Numerical Reasoning Skills in the Modular Approach for Complex Question Answering on Text
Xiao-Yu Guo, Yuan-Fang Li, Gholamreza Haffari
Numerical reasoning skills are essential for complex question answering (CQA) over text. It requires opertaions including counting, comparison, addition and subtraction. A successf…
Understanding Unnatural Questions Improves Reasoning over Text
Xiao-Yu Guo, Yuan-Fang Li, Gholamreza Haffari
Complex question answering (CQA) over raw text is a challenging task. A prominent approach to this task is based on the programmer-interpreter framework, where the programmer maps…