Search Results for author: Alexey Romanov

Found 19 papers, 5 papers with code

Lights, Camera, Action! A Framework to Improve NLP Accuracy over OCR documents

1 code implementation6 Aug 2021 Amit Gupte, Alexey Romanov, Sahitya Mantravadi, Dalitso Banda, Jianjie Liu, Raza Khan, Lakshmanan Ramu Meenal, Benjamin Han, Soundar Srinivasan

Document digitization is essential for the digital transformation of our societies, yet a crucial step in the process, Optical Character Recognition (OCR), is still not perfect.

Named Entity Recognition NER +1

Revealing the Dark Secrets of BERT

1 code implementation IJCNLP 2019 Olga Kovaleva, Alexey Romanov, Anna Rogers, Anna Rumshisky

BERT-based architectures currently give state-of-the-art performance on many NLP tasks, but little is known about the exact mechanisms that contribute to its success.

What's in a Name? Reducing Bias in Bios without Access to Protected Attributes

no code implementations NAACL 2019 Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai

In the context of mitigating bias in occupation classification, we propose a method for discouraging correlation between the predicted probability of an individual's true occupation and a word embedding of their name.

Word Embeddings

Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting

2 code implementations27 Jan 2019 Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai

We present a large-scale study of gender bias in occupation classification, a task where the use of machine learning may lead to negative outcomes on peoples' lives.

General Classification

Adversarial Decomposition of Text Representation

2 code implementations NAACL 2019 Alexey Romanov, Anna Rumshisky, Anna Rogers, David Donahue

We show that the proposed method is capable of fine-grained controlled change of these aspects of the input sentence.

Lessons from Natural Language Inference in the Clinical Domain

3 code implementations EMNLP 2018 Alexey Romanov, Chaitanya Shivade

State of the art models using deep neural networks have become very good in learning an accurate mapping from inputs to outputs.

Natural Language Inference Transfer Learning

RuSentiment: An Enriched Sentiment Analysis Dataset for Social Media in Russian

no code implementations COLING 2018 Anna Rogers, Alexey Romanov, Anna Rumshisky, Svitlana Volkova, Mikhail Gronas, Alex Gribov

This paper presents RuSentiment, a new dataset for sentiment analysis of social media posts in Russian, and a new set of comprehensive annotation guidelines that are extensible to other languages.

Active Learning General Classification +2

Forced Apart: Discovering Disentangled Representations Without Exhaustive Labels

no code implementations ICLR 2018 Alexey Romanov, Anna Rumshisky

Learning a better representation with neural networks is a challenging problem, which has been tackled from different perspectives in the past few years.

Tracking Bias in News Sources Using Social Media: the Russia-Ukraine Maidan Crisis of 2013--2014

no code implementations WS 2017 Peter Potash, Alexey Romanov, Anna Rumshisky, Mikhail Gronas

We show that on the task of predicting which side is likely to prefer a given article, a Naive Bayes classifier can record 90. 3{\%} accuracy looking only at domain names of the news sources.

SemEval-2017 Task 6: \#HashtagWars: Learning a Sense of Humor

no code implementations SEMEVAL 2017 Peter Potash, Alexey Romanov, Anna Rumshisky

This paper describes a new shared task for humor understanding that attempts to eschew the ubiquitous binary approach to humor detection and focus on comparative humor ranking instead.

Humor Detection

Forced to Learn: Discovering Disentangled Representations Without Exhaustive Labels

no code implementations1 May 2017 Alexey Romanov, Anna Rumshisky

Learning a better representation with neural networks is a challenging problem, which was tackled extensively from different prospectives in the past few years.

Here's My Point: Joint Pointer Architecture for Argument Mining

no code implementations EMNLP 2017 Peter Potash, Alexey Romanov, Anna Rumshisky

One of the major goals in automated argumentation mining is to uncover the argument structure present in argumentative text.

Argument Mining

Evaluating Creative Language Generation: The Case of Rap Lyric Ghostwriting

no code implementations WS 2018 Peter Potash, Alexey Romanov, Anna Rumshisky

The goal of this paper is to develop evaluation methods for one such task, ghostwriting of rap lyrics, and to provide an explicit, quantifiable foundation for the goals and future directions of this task.

Text Generation

#HashtagWars: Learning a Sense of Humor

no code implementations9 Dec 2016 Peter Potash, Alexey Romanov, Anna Rumshisky

Our best supervised system achieved 63. 7% accuracy, suggesting that this task is much more difficult than comparable humor detection tasks.

Humor Detection

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