1 citations · 1 across the 9 of their papers we have counts for
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Network World Models as Environments for Algorithm Design on Complex Systems
Rishab Alagharu, Hongji Pu, Zeeshan Memon +3
World models, which simulate an environment and predict how it changes under actions, are increasingly used in real-world applications such as robotics. Complex systems call for th…
AlgoBench: Benchmarking Algorithmic Adaptation in Code Generation
Xinyuan Song, Zekun Cai, Liang Zhao
High pass rates on established programming benchmarks such as HumanEval and LiveCodeBench do not always show whether a model can reason about algorithms. Many fixed benchmarks even…
AlgoSkill: Learning to Design Algorithms by Scheduling Human-Like Skills
Xinyuan Song, Zekun Cai, Liang Zhao
Designing an algorithm from a natural-language problem statement requires identifying the problem structure, reading constraints, choosing a suitable paradigm, checking correctness…
When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs
Xinyuan Song, Zekun Cai, Liang Zhao
Recursive self-training can degrade neural generative models when generated data is reused without fresh human data or external quality control. We study this risk in code LLMs, wh…
LUMINA: A Grid Foundation Model for Benchmarking AC Optimal Power Flow Surrogate Learning
Hongwei Jin, Keunju Song, Zeeshan Memon +5
AC optimal power flow (ACOPF) is foundational yet computationally expensive in power grid operations, driving learning-based surrogates for large-scale grid analysis. These surroga…
Towards Systematic Generalization for Power Grid Optimization Problems
Zeeshan Memon, Yijiang Li, Hongwei Jin +2
AC Optimal Power Flow (ACOPF) and Security-Constrained Unit Commitment (SCUC) are fundamental optimization problems in power system operations. ACOPF serves as the physical backbon…