Search Results for author: Eve Fleisig

Found 9 papers, 3 papers with code

Bilingual Lexical Access and Cognate Idiom Comprehension

1 code implementation COLING (CogALex) 2020 Eve Fleisig

Language transfer can facilitate learning L2 words whose form and meaning are similar to L1 words, or hinder speakers when the languages differ.

First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models

no code implementations8 Nov 2023 Naomi Saphra, Eve Fleisig, Kyunghyun Cho, Adam Lopez

Many NLP researchers are experiencing an existential crisis triggered by the astonishing success of ChatGPT and other systems based on large language models (LLMs).

Machine Translation

Incorporating Worker Perspectives into MTurk Annotation Practices for NLP

no code implementations6 Nov 2023 Olivia Huang, Eve Fleisig, Dan Klein

Current practices regarding data collection for natural language processing on Amazon Mechanical Turk (MTurk) often rely on a combination of studies on data quality and heuristics shared among NLP researchers.

Ghostbuster: Detecting Text Ghostwritten by Large Language Models

1 code implementation24 May 2023 Vivek Verma, Eve Fleisig, Nicholas Tomlin, Dan Klein

In conjunction with our model, we release three new datasets of human- and AI-generated text as detection benchmarks in the domains of student essays, creative writing, and news articles.

Centering the Margins: Outlier-Based Identification of Harmed Populations in Toxicity Detection

no code implementations24 May 2023 Vyoma Raman, Eve Fleisig, Dan Klein

We also find text and demographic outliers to be particularly susceptible to errors in the classification of severe toxicity and identity attacks.

Outlier Detection

When the Majority is Wrong: Modeling Annotator Disagreement for Subjective Tasks

no code implementations11 May 2023 Eve Fleisig, Rediet Abebe, Dan Klein

Thus, a crucial problem in hate speech detection is determining whether a statement is offensive to the demographic group that it targets, when that group may constitute a small fraction of the annotator pool.

Hate Speech Detection

Mitigating Gender Bias in Machine Translation through Adversarial Learning

no code implementations20 Mar 2022 Eve Fleisig, Christiane Fellbaum

Machine translation and other NLP systems often contain significant biases regarding sensitive attributes, such as gender or race, that worsen system performance and perpetuate harmful stereotypes.

Machine Translation Translation

Sentiment Analysis for Reinforcement Learning

no code implementations5 Oct 2020 Ameet Deshpande, Eve Fleisig

Furthermore, this can enable reinforcement learning without rewards, in which the agent learns entirely from these intrinsic sentiment rewards.

Dialogue Generation reinforcement-learning +3

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