Dan Klein

Policy Gradient as a Proxy for Dynamic Oracles in Constituency Parsing

2018

Dynamic oracles provide strong supervision for training constituency parsers with exploration, but must be custom defined for a given parser's transition system. We explore using a policy gradient method as a parser-agnostic alternative. In addition …

Automated Crossword Solving

2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Eric Wallace, Nicholas Tomlin, Albert Xu, Kevin Yang, Eshaan Pathak, Matthew Ginsberg, Dan Klein. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2022.

Constituency Parsing with a Self-Attentive Encoder

2018

We demonstrate that replacing an LSTM encoder with a self-attentive architecture can lead to improvements to a state-ofthe-art discriminative constituency parser. The use of attention makes explicit the manner in which information is propagated between …

Learning-Based Single-Document Summarization with Compression and Anaphoricity Constraints

2016

We present a discriminative model for single-document summarization that integrally combines compression and anaphoricity constraints.

Learning to Compose Neural Networks for Question Answering

2016

Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2016.

Multilingual Constituency Parsing with Self-Attention and Pre-Training

2019

We show that constituency parsing benefits from unsupervised pre-training across a variety of languages and a range of pre-training conditions. We first compare the benefits of no pre-training, fastText We also find that pre-training is …

A Minimal Span-Based Neural Constituency Parser

2017

In this work, we present a minimal neural model for constituency parsing based on independent scoring of labels and spans. We show that this model is not only compatible with classical dynamic programming techniques, but …

Multilingual Alignment of Contextual Word Representations

2020 · arXiv (Cornell University)

We propose procedures for evaluating and strengthening contextual embedding alignment and show that they are useful in analyzing and improving multilingual BERT. In particular, after our proposed alignment procedure, BERT exhibits significantly improved zero-shot performance …

Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level

2021

Larger language models have higher accuracy on average, but are they better on every single instance (datapoint)? Some work suggests larger models have higher out-ofdistribution robustness, while other work suggests they have lower accuracy on …