Haoming Jiang · PaperMetrix

BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision

2020

We study the open-domain named entity recognition (NER) problem under distant supervision. The distant supervision, though does not require large amounts of manual annotations, yields highly incomplete and noisy distant labels via external knowledge bases. …

ARCH: Efficient Adversarial Regularized Training with Caching

2021

Adversarial regularization can improve model generalization in many natural language processing tasks. However, conventional approaches are computationally expensive since they need to generate a perturbation for each sample in each epoch. We propose a new …

Token-wise Curriculum Learning for Neural Machine Translation

2021 · arXiv (Cornell University)

Existing curriculum learning approaches to Neural Machine Translation (NMT) require sampling sufficient amounts of "easy" samples from training data at the early training stage. This is not always achievable for low-resource languages where the amount …

SST: Semantic and Structural Transformers for Hierarchy-aware Language Models in E-commerce

2023

Hierarchies are common structures used to organize data, such as e-commerce hierarchies associated with product data. With these product hierarchies, we aim to learn hierarchy-aware product text embeddings to improve fine-tuning performance on a variety …

Robust Reinforcement Learning from Corrupted Human Feedback

2024 · arXiv (Cornell University)

Reinforcement learning from human feedback (RLHF) provides a principled framework for aligning AI systems with human preference data. For various reasons, e.g., personal bias, context ambiguity, lack of training, etc, human annotators may give incorrect …

BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering

2024