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cs.CL2026
TabScope: Question-Adaptive Scope Selection for Table Question Answering
Yuxiang Wang, Junhao Gan, Jianzhong Qi
Large Language Models (LLMs) have shown strong performance on table question answering, yet their accuracy often degrades as table size increases. We find that this degradation is…
cs.CL2026
Rethinking Stepwise Model Routing: A Cost-Efficient Table Reasoning Perspective
Shenghao Ye, Yuxiang Wang, Yu Guo +8
Large Reasoning Models (LRMs) achieve strong performance on table reasoning tasks but incur substantial inference cost due to long reasoning traces. Stepwise model routing mitigate…
cs.AI2026
Beyond Linearization: Attributed Table Graphs for Table Reasoning
Yuxiang Wang, Junhao Gan, Shengxiang Gao +3
Table reasoning, a task to answer questions by reasoning over data presented in tables, is an important topic due to the prevalence of knowledge stored in tabular formats. Recent s…