4 papers
Steerable Instruction Following Coding Data Synthesis with Actor-Parametric Schema Co-Evolution
Tinglin Huang, Bo Chen, Xiao Zhang +2
Interpreting and following human instructions is a critical capability of large language models (LLMs) in automatic programming. However, synthesizing large-scale instruction-paire…
AInsteinBench: Benchmarking Coding Agents on Scientific Repositories
Titouan Duston, Shuo Xin, Yang Sun +26
We introduce AInsteinBench, a large-scale benchmark for evaluating whether large language model (LLM) agents can operate as scientific computing development agents within real rese…
SWE-Mirror: Scaling Issue-Resolving Datasets by Mirroring Issues Across Repositories
Junhao Wang, Daoguang Zan, Shulin Xin +3
Creating large-scale verifiable training datasets for issue-resolving tasks is a critical yet notoriously difficult challenge. Existing methods on automating the Gym environment se…
CodeContests+: High-Quality Test Case Generation for Competitive Programming
Zihan Wang, Siyao Liu, Yang Sun +2
Competitive programming, due to its high reasoning difficulty and precise correctness feedback, has become a key task for both training and evaluating the reasoning capabilities of…