4 papers
PlanningBench: Generating Scalable and Verifiable Planning Data for Evaluating and Training Large Language Models
Ziliang Zhao, Zenan Xu, Shuting Wang +7
Planning is a fundamental capability for large language models (LLMs) because such complex tasks require models to coordinate goals, constraints, resources, and long-term consequen…
CL-bench Life: Can Language Models Learn from Real-Life Context?
Shihan Dou, Yujiong Shen, Chenhao Huang +35
Today's AI assistants such as OpenClaw are designed to handle context effectively, making context learning an increasingly important capability for models. As these systems move be…
Principal Context-aware Diffusion Guided Data Augmentation for Fault Localization
Shihao Fu, Yan Lei
Test cases are indispensable for conducting effective fault localization (FL). However, test cases in practice are severely class imbalanced, i.e. the number of failing test cases…
Revisiting and Improving Retrieval-Augmented Deep Assertion Generation
Weifeng Sun, Hongyan Li, Meng Yan +2
Unit testing validates the correctness of the unit under test and has become an essential activity in software development process. A unit test consists of a test prefix that drive…