4 citations · 5 across the 10 of their papers we have counts for
10 papers
Poisoning Agentic Alpha: Adversarial Vulnerabilities Across Roles and Architectures in Multi-Agent Trading Systems
CheolWon Na, Hao Ni, Lukasz Szpruch +7
LLM-based multi-agent trading systems, in which specialized agents collaborate through structured communication to produce trading decisions, are moving rapidly from research proto…
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…
MOSAIC: Modular Orchestration for Structured Agentic Intelligence and Composition
Yifan Bao, Xinyu Xi, Xinyu Liu +8
Automated data science is a structured model-selection problem. A solution must choose data transformations, feature representations, architecture, training procedure, evaluation p…
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…
MCGAN: Enhancing GAN Training with Regression-Based Generator Loss
Baoren Xiao, Hao Ni, Weixin Yang
Generative adversarial networks (GANs) have emerged as a powerful tool for generating high-fidelity data. However, the main bottleneck of existing approaches is the lack of supervi…
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…