4 citations · 6 across the 7 of their papers we have counts for
7 papers
Graph Evidence Is Not Enough: Diagnosing Native Decoder Use in Graph-Augmented LLMs
Xiaoyu Guo, Pengcheng Chen, Jiong Yu +3
Graph-augmented large language models often assume that graph evidence produced by external computation and placed in the input can be used by the native decoder. We test this assu…
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…
DeSIQ: Towards an Unbiased, Challenging Benchmark for Social Intelligence Understanding
Xiao-Yu Guo, Yuan-Fang Li, Gholamreza Haffari
Social intelligence is essential for understanding and reasoning about human expressions, intents and interactions. One representative benchmark for its study is Social Intelligenc…
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…