4 citations · 5 across the 7 of their papers we have counts for
7 papers
EvoTS-Agent: A Self-Evolving LLM Agent for Financial Time Series Change Point Detection
Lei Jiang, Ye Wei, Xinyu Xi +7
Financial time series exhibit non-stationary and heterogeneous statistical properties, making change-point detection challenging because no single unsupervised algorithm performs c…
OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents
Kaicheng Zhang, Wen Ge, Lei Jiang +5
Although large language model agents are increasingly applied to quantitative-finance workflows, their evaluation remains fragmented across isolated tasks, while the financial rele…
Sig-DEG for Distillation: Making Diffusion Models Faster and Lighter
Lei Jiang, Wen Ge, Niels Cariou-Kotlarek +7
Diffusion models achieve state-of-the-art generative performance but remain computationally expensive at inference, often requiring many discretization steps. We propose Sig-DEG (S…
Structured Agentic Workflows for Financial Time-Series Modeling with LLMs and Reflective Feedback
Yihao Ang, Yifan Bao, Lei Jiang +4
Time-series data is central to decision-making in financial markets, yet building high-performing, interpretable, and auditable models remains a major challenge. While Automated Ma…
MotionPCM: Real-Time Motion Synthesis with Phased Consistency Model
Lei Jiang, Ye Wei, Hao Ni
Diffusion models have become a popular choice for human motion synthesis due to their powerful generative capabilities. However, their high computational complexity and large sampl…
Using joint angles based on the international biomechanical standards for human action recognition and related tasks
Kevin Schlegel, Lei Jiang, Hao Ni
Keypoint data has received a considerable amount of attention in machine learning for tasks like action detection and recognition. However, human experts in movement such as doctor…
GCN-DevLSTM: Path Development for Skeleton-Based Action Recognition
Lei Jiang, Weixin Yang, Xin Zhang +1
Skeleton-based action recognition (SAR) in videos is an important but challenging task in computer vision. The recent state-of-the-art (SOTA) models for SAR are primarily based on…