101 citations · 158 across the 18 of their papers we have counts for
19 papers
STQA: A Benchmark for Stock-Focused Tabular Question Answering over Historical and Forecasted Data
Baoxu An, Wenmian Yang, Zhensheng Wang +1
Stock market analysis inherently requires composite reasoning over historical records and future projections, yet existing benchmarks remain fragmented across isolated tasks. We in…
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)…
ReCoQA: A Benchmark for Tool-Augmented and Multi-Step Reasoning in Real Estate Question and Answering
Yindong Zhang, Wenmian Yang, Yiquan Zhang +1
Developing agents capable of navigating fragmented, multi-source information remains challenging, primarily due to the scarcity of benchmarks reflecting hybrid workflows combining…
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…
TLCCSP: A Scalable Framework for Enhancing Time Series Forecasting with Time-Lagged Cross-Correlations
Jianfei Wu, Wenmian Yang, Bingning Liu +1
Time series forecasting is critical across various domains, such as weather, finance and real estate forecasting, as accurate forecasts support informed decision-making and risk mi…
HiGarment: Cross-modal Harmony Based Diffusion Model for Flat Sketch to Realistic Garment Image
Junyi Guo, Jingxuan Zhang, Fangyu Wu +5
Diffusion-based garment synthesis tasks primarily focus on the design phase in the fashion domain, while the garment production process remains largely underexplored. To bridge thi…
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…
Overcoming Negative Transfer by Online Selection: Distant Domain Adaptation for Fault Diagnosis
Ziyan Wang, Mohamed Ragab, Wenmian Yang +4
Unsupervised domain adaptation (UDA) has achieved remarkable success in fault diagnosis, bringing significant benefits to diverse industrial applications. While most UDA methods fo…
A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding
Lizhi Cheng, Wenmian Yang, Weijia Jia
Multi-Intent Spoken Language Understanding (SLU), a novel and more complex scenario of SLU, is attracting increasing attention. Unlike traditional SLU, each intent in this scenario…
Capture Salient Historical Information: A Fast and Accurate Non-Autoregressive Model for Multi-turn Spoken Language Understanding
Lizhi Cheng, Weijia jia, Wenmian Yang
Spoken Language Understanding (SLU), a core component of the task-oriented dialogue system, expects a shorter inference facing the impatience of human users. Existing work increase…
An Effective Non-Autoregressive Model for Spoken Language Understanding
Lizhi Cheng, Weijia Jia, Wenmian Yang
Spoken Language Understanding (SLU), a core component of the task-oriented dialogue system, expects a shorter inference latency due to the impatience of humans. Non-autoregressive…
A Result based Portable Framework for Spoken Language Understanding
Lizhi Cheng, Weijia Jia, Wenmian Yang
Spoken language understanding (SLU), which is a core component of the task-oriented dialogue system, has made substantial progress in the research of single-turn dialogue. However,…
On the Generation of Medical Dialogues for COVID-19
Wenmian Yang, Guangtao Zeng, Bowen Tan +9
Under the pandemic of COVID-19, people experiencing COVID19-related symptoms or exposed to risk factors have a pressing need to consult doctors. Due to hospital closure, a lot of c…
Interactive Variance Attention based Online Spoiler Detection for Time-Sync Comments
Wenmian Yang, Weijia Jia, Wenyuan Gao +2
Nowadays, time-sync comment (TSC), a new form of interactive comments, has become increasingly popular in Chinese video websites. By posting TSCs, people can easily express their f…
Legal Judgment Prediction via Multi-Perspective Bi-Feedback Network
Wenmian Yang, Weijia Jia, XIaojie Zhou +1
The Legal Judgment Prediction (LJP) is to determine judgment results based on the fact descriptions of the cases. LJP usually consists of multiple subtasks, such as applicable law…
Time-sync Video Tag Extraction Using Semantic Association Graph
Wenmian Yang, Kun Wang, Na Ruan +5
Time-sync comments reveal a new way of extracting the online video tags. However, such time-sync comments have lots of noises due to users' diverse comments, introducing great chal…
Herding Effect based Attention for Personalized Time-Sync Video Recommendation
Wenmian Yang, Wenyuan Gao, Xiaojie Zhou +3
Time-sync comment (TSC) is a new form of user-interaction review associated with real-time video contents, which contains a user's preferences for videos and therefore well suited…