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Found 4 papers, 2 papers with code
ConTest: A Unit Test Completion Benchmark featuring Context
We introduce CONTEST, a benchmark for NLP-based unit test completion, the task of predicting a test’s assert statements given its setup and focal method, i. e. the method to be tested.
Relation Specific Transformations for Open World Knowledge Graph Completion
We propose an open-world knowledge graph completion model that can be combined with common closed-world approaches (such as ComplEx) and enhance them to exploit text-based representations for entities unseen in training.
Addressing Leakage in Self-Supervised Contextualized Code Retrieval
We address contextualized code retrieval, the search for code snippets helpful to fill gaps in a partial input program.
An Open-World Extension to Knowledge Graph Completion Models
We present a novel extension to embedding-based knowledge graph completion models which enables them to perform open-world link prediction, i. e. to predict facts for entities unseen in training based on their textual description.
