4 citations · 8 across the 9 of their papers we have counts for
10 papers
From SEC Filings to Financial Signals: Evaluating LLMs on Stock Market Reactions and Analyst Forecasts
Shengkun Wang, Taoran Ji, Linhan Wang +3
Form 10-Q MD&A sections combine long-form management narrative with accounting and forward-looking information. Benchmarks for financial filings commonly evaluate question answerin…
SemiETPicker: Fast and Label-Efficient Particle Picking for CryoET Tomography Using Semi-Supervised Learning
Linhan Wang, Jianwen Dou, Wang Li +4
Cryogenic Electron Tomography (CryoET) combined with sub-volume averaging (SVA) is the only imaging modality capable of resolving protein structures inside cells at molecular resol…
HouseTS: A Large-Scale, Multimodal Spatiotemporal U.S. Housing Dataset and Benchmark
Shengkun Wang, Yanshen Sun, Fanglan Chen +4
Accurate long-horizon house-price forecasting requires benchmarks that capture temporal dynamics together with time-varying local context. However, existing public resources remain…
StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction
Shengkun Wang, Taoran Ji, Linhan Wang +4
The stock price prediction task holds a significant role in the financial domain and has been studied for a long time. Recently, large language models (LLMs) have brought new ways…
AMA-LSTM: Pioneering Robust and Fair Financial Audio Analysis for Stock Volatility Prediction
Shengkun Wang, Taoran Ji, Jianfeng He +5
Stock volatility prediction is an important task in the financial industry. Recent advancements in multimodal methodologies, which integrate both textual and auditory data, have de…
DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam Videos
Linhan Wang, Kai Cheng, Shuo Lei +5
We present DC-Gaussian, a new method for generating novel views from in-vehicle dash cam videos. While neural rendering techniques have made significant strides in driving scenario…
Stock Movement and Volatility Prediction from Tweets, Macroeconomic Factors and Historical Prices
Shengkun Wang, YangXiao Bai, Taoran Ji +3
Predicting stock market is vital for investors and policymakers, acting as a barometer of the economic health. We leverage social media data, a potent source of public sentiment, i…
JarviX: A LLM No code Platform for Tabular Data Analysis and Optimization
Shang-Ching Liu, ShengKun Wang, Wenqi Lin +6
In this study, we introduce JarviX, a sophisticated data analytics framework. JarviX is designed to employ Large Language Models (LLMs) to facilitate an automated guide and execute…
ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction
Shengkun Wang, YangXiao Bai, Kaiqun Fu +3
For both investors and policymakers, forecasting the stock market is essential as it serves as an indicator of economic well-being. To this end, we harness the power of social medi…
Self-Correlation and Cross-Correlation Learning for Few-Shot Remote Sensing Image Semantic Segmentation
Linhan Wang, Shuo Lei, Jianfeng He +3
Remote sensing image semantic segmentation is an important problem for remote sensing image interpretation. Although remarkable progress has been achieved, existing deep neural net…