7 papers
Diverse Evidence, Better Forecasts: Multi-Agent Deliberation Under Information Asymmetry
Yuante Li, Yicheng Tao, Kate Zhang +3
Multi-agent systems are increasingly used for forecasting future events, as deliberation among multiple LLMs is believed to improve reasoning and calibration. Yet existing approach…
MiniAppBench: Evaluating the Shift from Text to Interactive HTML Responses in LLM-Powered Assistants
Zuhao Zhang, Chengyue Yu, Yuante Li +3
With the rapid advancement of Large Language Models (LLMs) in code generation, human-AI interaction is evolving from static text responses to dynamic, interactive HTML-based applic…
Audio Language Model for Deepfake Detection Grounded in Acoustic Chain-of-Thought
Runkun Chen, Yixiong Fang, Pengyu Chang +3
Deepfake speech detection systems are often limited to binary classification tasks and struggle to generate interpretable reasoning or provide context-rich explanations for their d…
R&D-Agent: An LLM-Agent Framework Towards Autonomous Data Science
Xu Yang, Xiao Yang, Shikai Fang +13
Recent advances in AI and ML have transformed data science, yet increasing complexity and expertise requirements continue to hinder progress. Although crowd-sourcing platforms alle…
QuantMind: A Context-Engineering Based Knowledge Framework for Quantitative Finance
Haoxue Wang, Keli Wen, Yuante Li +11
Quantitative research increasingly relies on unstructured financial content such as filings, earnings calls, and research notes, yet existing LLM and RAG pipelines struggle with po…
R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
Yuante Li, Xu Yang, Xiao Yang +4
Financial markets pose fundamental challenges for asset return prediction due to their high dimensionality, non-stationarity, and persistent volatility. Despite advances in large l…