Integrating Multi-Source Feedback in Computational Design
本文探讨了通过实用方法和无代码工具MUSE整合多源反馈，以支持计算设计，增强设计师的信心与灵活性。
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Selected work
Representative Papers
Cooperative Risk-Aware Exploration in Heterogeneous Multi-Robot Systems Using Algorithmic Altruism
本文提出一种基于算法利他主义的游戏理论框架，解决异构多机器人系统在危险环境中的协作风险感知探索问题。
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FlyBlind: Cross-Slice Timeliness Attacks on UAV Situational Awareness over 5G
研究解决了5G网络中无人机态势感知的时效性攻击问题，通过FlyBlind方法展示了合法共租户如何导致地面控制站状态老化而不被传统监控手段发现。
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Aray: Deterministic-First Synthesis of Benign Artifacts for YARA Validation
为解决YARA规则验证中恶意样本难以分发的问题，本文提出Aray，一种确定性优先的YARA解释器和正向样本合成器，有效生成非恶意但符合规则的文件用于验证。
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OptiAgent: End-to-End Optimization Modeling via Multi-Agent Iterative Refinement
This work proposes a multi-agent collaborative framework that automatically translates natural language descriptions of operations research problems into solvable mathematical models and executable code. To address common modeling challenges—such as semantic misinterpretation, structural flaws, and mathematical inconsistencies—the approach employs specialized agents to extract decision variables and constraints, integrating structured information extraction, iterative self-correction, and a fourfold feedback validation mechanism to achieve end-to-end modeling. Its modular architecture enhances transparency and auditability throughout the modeling process. Evaluated on four standard benchmarks encompassing linear programming (LP), mixed-integer linear programming (MILP), and nonlinear programming, the method achieves state-of-the-art performance on three and demonstrates highly competitive results on the fourth.
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Latest Papers
Integrating Multi-Source Feedback in Computational Design
本文探讨了通过实用方法和无代码工具MUSE整合多源反馈，以支持计算设计，增强设计师的信心与灵活性。
0 citationsRead paper
Cooperative Risk-Aware Exploration in Heterogeneous Multi-Robot Systems Using Algorithmic Altruism
本文提出一种基于算法利他主义的游戏理论框架，解决异构多机器人系统在危险环境中的协作风险感知探索问题。
0 citationsRead paper
FlyBlind: Cross-Slice Timeliness Attacks on UAV Situational Awareness over 5G
研究解决了5G网络中无人机态势感知的时效性攻击问题，通过FlyBlind方法展示了合法共租户如何导致地面控制站状态老化而不被传统监控手段发现。
0 citationsRead paper
Aray: Deterministic-First Synthesis of Benign Artifacts for YARA Validation
为解决YARA规则验证中恶意样本难以分发的问题，本文提出Aray，一种确定性优先的YARA解释器和正向样本合成器，有效生成非恶意但符合规则的文件用于验证。
0 citationsRead paper
OptiAgent: End-to-End Optimization Modeling via Multi-Agent Iterative Refinement
This work proposes a multi-agent collaborative framework that automatically translates natural language descriptions of operations research problems into solvable mathematical models and executable code. To address common modeling challenges—such as semantic misinterpretation, structural flaws, and mathematical inconsistencies—the approach employs specialized agents to extract decision variables and constraints, integrating structured information extraction, iterative self-correction, and a fourfold feedback validation mechanism to achieve end-to-end modeling. Its modular architecture enhances transparency and auditability throughout the modeling process. Evaluated on four standard benchmarks encompassing linear programming (LP), mixed-integer linear programming (MILP), and nonlinear programming, the method achieves state-of-the-art performance on three and demonstrates highly competitive results on the fourth.
0 citationsRead paper