6 papers
ODTQA-FoRe: An Open-Domain Tabular Question Answering Dataset for Future Data Forecasting and Reasoning
Zhensheng Wang, Xiaole Liu, Wenmian Yang +3
The rapid development of LLMs has significantly advanced tabular question answering, but most systems cannot perform future-oriented numerical prediction. To address this gap, we i…
BacktestBench: Benchmarking Large Language Models for Automated Quantitative Strategy Backtesting
Zhensheng Wang, Wenmian Yang, Qingtai Wu +3
Quantitative backtesting is essential for evaluating trading strategies but remains hampered by high technical barriers and limited scalability. While Large Language Models (LLMs)…
Automatic Slide Updating with User-Defined Dynamic Templates and Natural Language Instructions
Kun Zhou, Jiakai He, Wenmian Yang +3
Presentation slides are a primary medium for data-driven reporting, yet keeping complex, analytics-style decks up to date remains labor-intensive. Existing automation methods mostl…
ODUTQA-MDC: A Task for Open-Domain Underspecified Tabular QA with Multi-turn Dialogue-based Clarification
Zhensheng Wang, ZhanTeng Lin, Wenmian Yang +3
The advancement of large language models (LLMs) has enhanced tabular question answering (Tabular QA), yet they struggle with open-domain queries exhibiting underspecified or uncert…
EVGeoQA: Benchmarking LLMs on Dynamic, Multi-Objective Geo-Spatial Exploration
Jianfei Wu, Zhichun Wang, Zhensheng Wang +1
While Large Language Models (LLMs) demonstrate remarkable reasoning capabilities, their potential for purpose-driven exploration in dynamic geo-spatial environments remains under-i…
RETQA: A Large-Scale Open-Domain Tabular Question Answering Dataset for Real Estate Sector
Zhensheng Wang, Wenmian Yang, Kun Zhou +2
The real estate market relies heavily on structured data, such as property details, market trends, and price fluctuations. However, the lack of specialized Tabular Question Answeri…