4 citations · 7 across the 14 of their papers we have counts for
16 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…
Wiring Matters: Injection Topology and Initialization of Affordance Heads in Vision-Language-Action Policies
Zijian An, Linhan Wang, Jiayan Wang +4
Dense affordance supervision is an appealing auxiliary signal for vision-language-action (VLA) policies, yet naively co-training an affordance head can severely damage instruction…
GlanceWAM: Sparse Test-Time Imagination for World-Action Models
Linhan Wang, Zijian An, Mingyuan Zhang +8
Video generative models provide rich physical priors for robot learning, yet existing world-action models (WAMs) face a fundamental trade-off: synchronous video generation at contr…
RSC: Decentralized Rigid Formation Flocking for Large-Scale Swarms via Hybrid Predictive Control and Online Reconfiguration
Ganyu Zou, Linhan Wang, Chen Dai +2
Decentralized rigid formation flocking requires a swarm of autonomous agents to maintain a predetermined geometric configuration while moving, relying solely on local sensing and c…
Drive-JEPA: Video JEPA Meets Multimodal Trajectory Distillation for End-to-End Driving
Linhan Wang, Zichong Yang, Chen Bai +6
End-to-end autonomous driving increasingly leverages self-supervised video pretraining to learn transferable planning representations. However, pretraining video world models for s…
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…
Chasing the Timber Trail: Machine Learning to Reveal Harvest Location Misrepresentation
Shailik Sarkar, Raquib Bin Yousuf, Linhan Wang +9
Illegal logging poses a significant threat to global biodiversity, climate stability, and depresses international prices for legal wood harvesting and responsible forest products t…
Downscaling Precipitation with Bias-informed Conditional Diffusion Model
Ran Lyu, Linhan Wang, Yanshen Sun +2
Climate change is intensifying rainfall extremes, making high-resolution precipitation projections crucial for society to better prepare for impacts such as flooding. However, curr…
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…
Can LLM find the green circle? Investigation and Human-guided tool manipulation for compositional generalization
Min Zhang, Jianfeng He, Shuo Lei +3
The meaning of complex phrases in natural language is composed of their individual components. The task of compositional generalization evaluates a model's ability to understand ne…
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…
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…