Bei Chen

Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation

2016 · Proceedings of the AAAI Conference on Artificial Intelligence

We present a discriminative nonparametric latent feature relational model (LFRM) for link prediction to automatically infer the dimensionality of latent features. Under the generic RegBayes (regularized Bayesian inference) framework, we handily incorporate the prediction loss …

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 …