4 papers
Can LLMs Reason Structurally? Benchmarking via the Lens of Data Structures
Yu He, Yingxi Li, Colin White +1
Large language models (LLMs) are deployed on increasingly complex tasks that require multi-step decision-making. Understanding their algorithmic reasoning abilities is therefore cr…
Smoothed Analysis of Online Metric Matching with a Single Sample: Beyond Metric Distortion
Yingxi Li, Ellen Vitercik, Mingwei Yang
In the online metric matching problem, servers and requests lie in a metric space. Servers are available upfront, and requests arrive sequentially. An arriving request must…
Accelerating data-driven algorithm selection for combinatorial partitioning problems
Vaggos Chatziafratis, Ishani Karmarkar, Yingxi Li +1
Data-driven algorithm selection is a powerful approach for choosing effective heuristics for computational problems. It operates by evaluating a set of candidate algorithms on a co…
LLMs for Cold-Start Cutting Plane Separator Configuration
Connor Lawless, Yingxi Li, Anders Wikum +2
Mixed integer linear programming (MILP) solvers expose hundreds of parameters that have an outsized impact on performance but are difficult to configure for all but expert users. E…