From the 1 of 18 linked papers with an AI index.
18 papers
AQuA: Recursively Self-Improving Quantitative Trading Research Agents
Jiacheng Guo, Suozhi Huang, Yunlong Gao +5
We study recursive self-improvement at the level of quantitative-investment research: whether an autonomous system can use evidence from earlier experiments to improve the hypothes…
DeepLoop: Depth Scaling for Looped Transformers
Shuzhen Li, Yifan Zhang, Jiacheng Guo +2
DeepLoop reuses a compact stack of transformer blocks across multiple passes to increase model depth without adding parameters, and introduces new residual scaling rules to keep tr…
Stealthy Multi-Task Adversarial Attacks
Jiacheng Guo, Tianyun Zhang, Lei Li +3
Deep neural networks are highly vulnerable to adversarial perturbations, raising serious safety concerns in the real-world systems. While prior work mainly explores single-task att…
CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency
Jiacheng Guo, Suozhi Huang, Zixin Yao +16
This paper introduces CryptoBench, the first expert-curated, dynamic benchmark designed to rigorously evaluate the real-world capabilities of Large Language Model (LLM) agents in t…
Unsupervised Multi-agent and Single-agent Perception from Cooperative Views
Haochen Yang, Baolu Li, Lei Li +5
The LiDAR-based multi-agent and single-agent perception has shown promising performance in environmental understanding for robots and automated vehicles. However, there is no exist…
FutureX-Pro: Extending Future Prediction to High-Value Vertical Domains
Jiashuo Liu, Siyuan Chen, Zaiyuan Wang +38
Building upon FutureX, which established a live benchmark for general-purpose future prediction, this report introduces FutureX-Pro, including FutureX-Finance, FutureX-Retail, Futu…