Jian–Guang Lou

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 …

Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation

2019

We present a neural approach called IRNet for complex and cross-domain Text-to-SQL. IR-Net aims to address two challenges: 1) the mismatch between intents expressed in natural language (NL) and the implementation details in SQL; 2) …

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 …