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ORCID11th IDS 2025: New York, NY, USA
- 11th IEEE International Conference on Intelligent Data and Security, IDS 2025, New York City, NY, USA, May 9-11, 2025. IEEE 2025, ISBN 979-8-3315-9661-3
- Javad Mokhtari Koushyar
, Mina Guirguis, George K. Atia:
The Role of Aggregator Topology on the Impact of False Data Injection Attacks. 1-4 - Kishan Baranwal, Haresh Dagale:
A survey of ML Resources for IEC 61850 in Power Grid Security. 5-14 - Chen Zhang, Ling Wang, Hanyu Rao, Xiaojun Shen, Yiliang Wang, Kun Tong:
A Code Embedding-Based Java Software Risk Detection Method. 15-20 - Sepideh Neshatfar, Salimeh Yasaei Sekeh:
Robust Subgraph Learning by Monitoring Early Training Representations. 21-32 - Jichao Ye, Hui Huang, Aoying Ji, Wu Lu, Yonghai Xu, Ping Wang:
Multi-Factor Authentication Key Pre-Distribution Scheme for Security Isolation System of Next Hop Resolution Protocol. 33-38 - Faten Slama, Daniel Lemire:
Enhancing Developer Productivity: Benchmarking LLM-Powered Tools like GitHub Copilot and TabNine in Real-Time Coding Environments. 39-45 - Ruijian Zha, Bojun Liu:
A New DAPO Algorithm for Stock Trading. 46-48 - Yan Wang, Yueru He, Ruoyu Xiang, Jeff Zhao:
RKEFino1: A Regulation Knowledge-Enhanced Large Language Model. 49-51 - Satish Chandra, G. Balakrishna:
Enhancing FinRL Trading Agents with Advance LLM-Processed Financial News: An Improved Approach Using DeepSeek-V3. 52-54 - Jun-Chi Liu, Junchao Ma, Zhi-Qiang Jiang:
AlphaSeek FinRL: A Hybrid Deep Learning Architecture for High-Frequency Cryptocurrency Trading. 55-57 - Varun Rao, Youran Sun, Mahendra Kumar, Tejas Mutneja, Agastya Mukherjee, Haizhao Yang:
LLMs Meet Finance: Fine-Tuning Foundation Models for the Open FinLLM Leaderboard. 58-61 - Shenjian Li, Mingxuan Yu, Freddie Dossor:
Option-Driven Sentiment in FinRL: a PPO Approach to Trading. 62-64 - Keyi Wang, Kairong Xiao, Xiao-Yang Liu Yanglet:
Parallel Market Environments for FinRL Contests. 65-67 - Jean Ndoutoumou, Zining Yin, Xiaochang Cheng:
HMM-Based Market Regime Detection with RL for Portfolio Management. 68-70 - Vorakorn Kosidphokin, Phawat Loedtrakunchai, Natthakorn Sinamnuaiphon, Surawit Kuptanon:
FinRL: Adaptive Model Selection for Reinforcement Learning in Stock Trading. 71-72 - Pavel Voropaev, Anna Detkina:
Advancing Financial Standards Comprehension through Domain-Specific MoE Architecture. 73-75 - Sahar Arshad, Huma Ameer, Nikhar Azhar, Seemab Latif:
FinRL Contest 2025 Task 1: Market-Aware In-Context Learning Framework for Proximal Policy Optimization in Stock Trading Using DeepSeek. 76-78 - Emran Y. Alturki, Aydin Javadov, Qiyang Sun, Björn W. Schuller:
Adaptive Confidence-Weighted LLM Infusion for Financial Reinforcement Learning. 79-82
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