From the 1 of 10 linked papers with an AI index.
5 papers · 1 filter
Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model Behavior
Rahul Nadkarni, Yanai Elazar, Hila Gonen +1
We present an experimental recipe for studying the relationship between training data and language model (LM) behavior. We outline steps for intervening on data batches -- i.e., ``…
Evaluating -Gram Novelty of Language Models Using Rusty-DAWG
William Merrill, Noah A. Smith, Yanai Elazar
How novel are texts generated by language models (LMs) relative to their training corpora? In this work, we investigate the extent to which modern LMs generate -grams from their…
On Linear Representations and Pretraining Data Frequency in Language Models
Jack Merullo, Noah A. Smith, Sarah Wiegreffe +1
Pretraining data has a direct impact on the behaviors and quality of language models (LMs), but we only understand the most basic principles of this relationship. While most work f…
Paloma: A Benchmark for Evaluating Language Model Fit
Ian Magnusson, Akshita Bhagia, Valentin Hofmann +13
Evaluations of language models (LMs) commonly report perplexity on monolithic data held out from training. Implicitly or explicitly, this data is composed of domains--varying distr…
Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals
Yanai Elazar, Bhargavi Paranjape, Hao Peng +5
The inevitable appearance of spurious correlations in training datasets hurts the generalization of NLP models on unseen data. Previous work has found that datasets with paired inp…