Papers by Jiaqi Shi
HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation (2022.acl-long)
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Zhoujun Cheng, Haoyu Dong, Zhiruo Wang, Ran Jia, Jiaqi Guo, Yan Gao, Shi Han, Jian-Guang Lou, Dongmei Zhang
| Challenge: | Existing studies on table reasoning focus on flat tables and hierarchical tables . a new dataset, HiTab, aims to examine numerical reasoning over hierarchic tables based on hierarchically structured tables - a strong challenge for existing baselines and a valuable benchmark for future research. |
| Approach: | They propose a hierarchical question answering and natural language generation dataset to study hierarchic tables. |
| Outcome: | The proposed model shows that it is effective in QA and natural language generation over hierarchical tables. |
From Inheritance to Saturation: Disentangling the Evolution of Visual Redundancy for Architecture-Aware MLLM Inference Acceleration (2026.acl-long)
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| Challenge: | Existing acceleration strategies suffer from severe "backbone dependency" Existing strategies such as token pruning or layer sparsity suffer from this . |
| Approach: | They propose a framework that decouples visual redundancy into IVR and architecture-dependent secondary saturation redundancies. |
| Outcome: | The proposed framework outperforms existing frameworks on Qwen25-VL and Qwa25-LL. |