4 citations · 6 across the 12 of their papers we have counts for
14 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…
ReCast: Contract-Preserving Protection for Fixed-Interface Multimodal Reasoning
Bingchen Pei, Lichong Chen, Bingxi Zhao +8
Remote multimodal models offer strong numerical reasoning capabilities over charts and speech, but sending private inputs risks exposing sensitive content. Text-only sanitization c…
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…
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…
Collaborative LLM Numerical Reasoning with Local Data Protection
Min Zhang, Yuzhe Lu, Yun Zhou +4
Numerical reasoning over documents, which demands both contextual understanding and logical inference, is challenging for low-capacity local models deployed on computation-constrai…
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…
Don't Go To Extremes: Revealing the Excessive Sensitivity and Calibration Limitations of LLMs in Implicit Hate Speech Detection
Min Zhang, Jianfeng He, Taoran Ji +1
The fairness and trustworthiness of Large Language Models (LLMs) are receiving increasing attention. Implicit hate speech, which employs indirect language to convey hateful intenti…
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…
Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission
Jianfeng He, Linlin Yu, Shuo Lei +2
Sequential labeling is a task predicting labels for each token in a sequence, such as Named Entity Recognition (NER). NER tasks aim to extract entities and predict their labels giv…
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…