TaPERA: Enhancing Faithfulness and Interpretability in Long-Form Table QA by Content Planning and Execution-based Reasoning
Yilun Zhao, Lyuhao Chen, Arman Cohan, Chen Zhao
Abstract
Long-form Table Question Answering (LFTQA) requires systems to generate paragraph long and complex answers to questions over tabular data. While Large language models based systems have made significant progress, it often hallucinates, especially when the task involves complex reasoning over tables. To tackle this issue, we propose a new LLM-based framework, TAPERA, for LFTQA tasks. Our framework uses a modular approach that decomposes the whole process into three sub-modules: 1) QA-based Content Planner that iteratively decomposes the input question into sub-questions; 2) Execution-based Table Reasoner that produces executable Python program for each sub-question; and 3) Answer Generator that generates long-form answer grounded on the program output. Human evaluation results on the FETAQA and QTSUMM datasets indicate that our framework significantly improves strong baselines on both accuracy and truthfulness, as our modular framework is better at table reasoning, and the long-form answer is always consistent with the program output. Our modular design further provides transparency as users are able to interact with our framework by manually changing the content plans. https://github.com/yilunzhao/TaPERA Plan-based Answer Generation Direct Answer Generation Q1: Which company earns the highest profit in the Oil and Gas industry? A1: Sinopec Group earns the highest profit in the Oil and Gas industry. Q2: Which company earns the overall highest profit? A2: Apple earns the overall highest profit. Q3: Compare these two companies. A3: [pending] Q1: Which company earns the highest profit in the Oil and Gas industry? A1: Sinopec Group earns the highest profit in the Oil and Gas industry. Q2: Which company earns the overall highest profit? A2: Apple earns the overall highest profit. Q3: Compare these two companies. A3: Apple is in the electronics industry, while Sinopec Group is in the Oil and Gas industry.
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