Zeqi Lin

Adaptive Deep Code Search

2020

Searching code in a large-scale codebase using natural language queries is a common practice during software development. Deep learning-based code search methods demonstrate superior performance if models are trained with large amount of text-code pairs. …

Learning Algebraic Recombination for Compositional Generalization

2021 · arXiv (Cornell University)

Neural sequence models exhibit limited compositional generalization ability in semantic parsing tasks. Compositional generalization requires algebraic recombination, i.e., dynamically recombining structured expressions in a recursive manner. However, most previous studies mainly concentrate on recombining lexical …

Making Large Language Models Better Reasoners with Step-Aware Verifier

2022 · arXiv (Cornell University)

Few-shot learning is a challenging task that requires language models to generalize from limited examples. Large language models like GPT-3 and PaLM have made impressive progress in this area, but they still face difficulties in …