On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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5 results for “gender-neutral”

Learning Gender-Neutral Word Embeddingscs.CL

Paper proposes GN-GloVe to learn gender-neutral word embeddings.

problem Inherit strong gender stereotypes in embeddings trained on human-generated corpora.

method Proposes a novel training procedure to isolate gender information in word vectors.

result GN-GloVe successfully isolates gender information without sacrificing functionality.

word embeddings gender stereotypes gender-neutral Natural Language Processing embedding models

2018-08-29abs ↗pdf ↗

How to Measure Gender Bias in Machine Translation: Optimal Translators, Multiple Reference Pointsstat.ML

Study measures gender bias in machine translation using multiple reference points.

problem Measuring and identifying gender bias in machine translation.

method Used an optimal non-biased translator, reference points from occupational statistics and survey.

result Found bias against both genders, but more against women, and found occupations have a greater effect than adjectives.

gender bias machine translation occupational statistics survey optimal translator

2020-11-12abs ↗pdf ↗

Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generationcs.CL

New method neutralizes gender bias in word embeddings without losing semantic information.

problem Gender biases in word embeddings trained on human-generated corpora.

method Latent Disentanglement and Counterfactual Generation with siamese auto-encoder and gradient reversal layer.

result Our method outperforms existing debiasing methods in preserving semantic information and neutralizing gender biases.

word embeddings gender bias latent disentanglement counterfactual generation semantic information

2020-04-07abs ↗pdf ↗

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscs.CL

The blind application of machine learning runs the risk of amplifying biases present in data. Such a danger is facing us with word embedding, a popular framework to represent text data as vectors which has been used in many machine learning and natural language processing tasks. We show that even word embeddings traine…

2016-07-21abs ↗pdf ↗

Marginal Fairness: Fair Decision-Making under Risk Measuresstat.ML

New fairness criterion for risk-sensitive decisions in regulated industries.

problem Ensuring equitable outcomes in risk-sensitive decision-making.

method Marginal fairness for generalized distortion risk measures, two-step decision-making process.

result Ensures fairness in decision-making under risk measures, regardless of protected attributes.

fairness risk measures regulated industries individual fairness cascade sensitivity

2025-05-24abs ↗pdf ↗