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Found 11 papers, 9 papers with code
Gender and Representation Bias in GPT-3 Generated Stories
Using topic modeling and lexicon-based word similarity, we find that stories generated by GPT-3 exhibit many known gender stereotypes.
On Classification with Large Language Models in Cultural Analytics
In this work, we survey the way in which classification is used as a sensemaking practice in cultural analytics, and assess where large language models can fit into this landscape.
Mathfish: Evaluating Language Model Math Reasoning via Grounding in Educational Curricula
To ensure that math curriculum is grade-appropriate and aligns with critical skills or concepts in accordance with educational standards, pedagogical experts can spend months carefully reviewing published math problems.
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
As a result, it is challenging to conduct and advance scientific research on language modeling, such as understanding how training data impacts model capabilities and limitations.
AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters
Large language models' (LLMs) abilities are drawn from their pretraining data, and model development begins with data curation.
"One-Size-Fits-All"? Examining Expectations around What Constitute "Fair" or "Good" NLG System Behaviors
Fairness-related assumptions about what constitute appropriate NLG system behaviors range from invariance, where systems are expected to behave identically for social groups, to adaptation, where behaviors should instead vary across them.
Words as Gatekeepers: Measuring Discipline-specific Terms and Meanings in Scholarly Publications
Scholarly text is often laden with jargon, or specialized language that can facilitate efficient in-group communication within fields but hinder understanding for out-groups.
Discovering Differences in the Representation of People using Contextualized Semantic Axes
A common paradigm for identifying semantic differences across social and temporal contexts is the use of static word embeddings and their distances.
Characterizing English Variation across Social Media Communities with BERT
Much previous work characterizing language variation across Internet social groups has focused on the types of words used by these groups.
Using Sentiment Induction to Understand Variation in Gendered Online Communities
We analyze gendered communities defined in three different ways: text, users, and sentiment.
Are distributional representations ready for the real world? Evaluating word vectors for grounded perceptual meaning
Distributional word representation methods exploit word co-occurrences to build compact vector encodings of words.
