most citedTradingGroup: A Multi-Agent Trading System with Self-Reflection and Data-Synthesis

1 citations · 1 across the 4 of their papers we have counts for

collaborators

11 papers

cs.AI2025

SOCIA-Nabla: Textual Gradient Meets Multi-Agent Orchestration for Automated Simulator Generation

Yuncheng Hua, Sion Weatherhead, Mehdi Jafari +2

In this paper, we present SOCIA-Nabla, an end-to-end, agentic framework that treats simulator construction asinstance optimization over code within a textual computation graph. Spe…

cs.AI20251 cited

TradingGroup: A Multi-Agent Trading System with Self-Reflection and Data-Synthesis

Feng Tian, Flora D. Salim, Hao Xue

Recent advancements in large language models (LLMs) have enabled powerful agent-based applications in finance, particularly for sentiment analysis, financial report comprehension,…

cs.SD2025

CoughViT: A Self-Supervised Vision Transformer for Cough Audio Representation Learning

Justin Luong, Hao Xue, Flora D. Salim

Physicians routinely assess respiratory sounds during the diagnostic process, providing insight into the condition of a patient's airways. In recent years, AI-based diagnostic syst…

cs.CV2025

Bisecle: Binding and Separation in Continual Learning for Video Language Understanding

Yue Tan, Xiaoqian Hu, Hao Xue +2

Frontier vision-language models (VLMs) have made remarkable improvements in video understanding tasks. However, real-world videos typically exist as continuously evolving data stre…

cs.CV2025

Generate the Forest before the Trees -- A Hierarchical Diffusion model for Climate Downscaling

Declan J. Curran, Sanaa Hobeichi, Hira Saleem +2

Downscaling is essential for generating the high-resolution climate data needed for local planning, but traditional methods remain computationally demanding. Recent years have seen…

cs.AI2025

Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning

Ruiyi Yang, Hao Xue, Imran Razzak +3

Retrieval-Augmented Generation (RAG) systems empower large language models (LLMs) with external knowledge, yet struggle with efficiency-accuracy trade-offs when scaling to large kn…