Roy Schwartz

Automatic Selection of Context Configurations for Improved Class-Specific Word Representations

2017

This paper is concerned with identifying contexts useful for training word representation models for different word classes such as adjectives (A), verbs (V), and nouns (N). We introduce a simple yet effective framework for an …

Correlated Rounding of Multiple Uniform Matroids and Multi-Label Classification

2017 · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

We introduce correlated randomized dependent rounding where, given multiple points y^1,...,y^n in some polytope P\subseteq [0,1]^k, the goal is to simultaneously round each y^i to some integral z^i in P while preserving both marginal values …

Expected Validation Performance and Estimation of a Random Variable's Maximum

2021 · arXiv (Cornell University)

Research in NLP is often supported by experimental results, and improved reporting of such results can lead to better understanding and more reproducible science. In this paper we analyze three statistical estimators for expected validation …

Symmetric Pattern Based Word Embeddings for Improved Word Similarity Prediction

2015

We present a novel word level vector representation based on symmetric patterns (SPs). For this aim we automatically acquire SPs (e.g., "X and Y") from a large corpus of plain text, and generate vectors where …

Annotation Artifacts in Natural Language Inference Data

2018

Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel Bowman, Noah A. Smith. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short …

SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

2018

Given a partial description like "she opened the hood of the car," humans can reason about the situation and anticipate what might come next ("then, she examined the engine"). In this paper, we introduce the …

A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications

2018

Dongyeop Kang, Waleed Ammar, Bhavana Dalvi, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard Hovy, Roy Schwartz. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume …

Show Your Work: Improved Reporting of Experimental Results

2019

Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, Noah A. Smith. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

Knowledge Enhanced Contextual Word Representations

2019

Matthew E. Peters, Mark Neumann, Robert Logan, Roy Schwartz, Vidur Joshi, Sameer Singh, Noah A. Smith. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on …

Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping

2020 · arXiv (Cornell University)

Fine-tuning pretrained contextual word embedding models to supervised downstream tasks has become commonplace in natural language processing. This process, however, is often brittle: even with the same hyperparameter values, distinct random seeds can lead to …