5 papers
Analyzing the Difficulty of Programming Assignments with Interpretable Knowledge Component Metrics
Tsvetomila Mihaylova, Jing Fan, Bita Akram +4
This research paper examines how Knowledge Components (KCs) - fine-grained concepts or skills required to solve programming tasks - can be used as interpretable signals for underst…
Orthogonal Hierarchical Decomposition for Structure-Aware Table Understanding with Large Language Models
Bin Cao, Huixian Lu, Chenwen Ma +3
Complex tables with multi-level headers, merged cells and heterogeneous layouts pose persistent challenges for LLMs in both understanding and reasoning. Existing approaches typical…
Principles and Practices of Large-Scale Code Analysis at Ant Group: A Data- and Logic-Oriented Approach
Xiaoheng Xie, Gang Fan, Xiaojun Lin +21
Large-scale software development requires dynamic and multifaceted static code analysis that extends beyond the capabilities of traditional tools. Existing tools like CodeQL lack c…
PRISM: A Benchmark for Programmatic Spatial-Temporal Reasoning
Qiran Zhang, Yuheng Wang, Runde Yang +9
Programmatic video generation through code offers geometric precision and temporal coherence beyond pixel-level diffusion models, yet rigorously evaluating whether language models…
The Effects of Structured LLM-Generated Feedback on Programming Assignment Performance
Tsvetomila Mihaylova, Evanfiya Logacheva, Arto Hellas +6
When programming students encounter errors in their code, compiler messages or static analysis output often provide limited guidance, particularly for novice programmers. Personali…