7 citations · 26 across the 25 of their papers we have counts for
9 papers · 1 filter
FinAbstain: Uncertainty-Calibrated Multimodal RAG for Selective Financial Forecasting
Dorothy Torres, Wei Cheng, Henan Huang
Large language models (LLMs) can synthesize financial narratives but may express high confidence when evidence is sparse, stale, or contradictory. This failure is especially conseq…
xTime: Extreme Event Prediction with Hierarchical Knowledge Distillation and Expert Fusion
Quan Li, Wenchao Yu, Suhang Wang +4
Extreme events frequently occur in real-world time series and often carry significant practical implications. In domains such as climate and healthcare, these events, such as flood…
SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search
Dong Li, Xujiang Zhao, Linlin Yu +7
Large Language Models (LLMs) offer promising capabilities for tackling complex reasoning tasks, including optimization problems. However, existing methods either rely on prompt eng…
Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting
ChengAo Shen, Wenchao Yu, Ziming Zhao +4
Time series, typically represented as numerical sequences, can also be transformed into images and texts, offering multi-modal views (MMVs) of the same underlying signal. These MMV…
Where's the liability in the Generative Era? Recovery-based Black-Box Detection of AI-Generated Content
Haoyue Bai, Yiyou Sun, Wei Cheng +1
The recent proliferation of photorealistic images created by generative models has sparked both excitement and concern, as these images are increasingly indistinguishable from real…
TimeXL: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop
Yushan Jiang, Wenchao Yu, Geon Lee +5
Time series analysis provides essential insights for real-world system dynamics and informs downstream decision-making, yet most existing methods often overlook the rich contextual…