1 citations · 1 across the 7 of their papers we have counts for
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Benchmarking Debiasing Methods for LLM-based Parameter Estimates
Nicolas Audinet de Pieuchon, Adel Daoud, Connor T. Jerzak +2
Large language models (LLMs) offer an inexpensive yet powerful way to annotate text, but are often inconsistent when compared with experts. These errors can bias downstream estimat…
Identifying Non-Replicable Social Science Studies with Language Models
Denitsa Saynova, Kajsa Hansson, Bastiaan Bruinsma +2
In this study, we investigate whether LLMs can be used to indicate if a study in the behavioural social sciences is replicable. Using a dataset of 14 previously replicated studies…
Fact Recall, Heuristics or Pure Guesswork? Precise Interpretations of Language Models for Fact Completion
Denitsa Saynova, Lovisa Hagström, Moa Johansson +2
Language models (LMs) can make a correct prediction based on many possible signals in a prompt, not all corresponding to recall of factual associations. However, current interpreta…
Can Large Language Models (or Humans) Disentangle Text?
Nicolas Audinet de Pieuchon, Adel Daoud, Connor Thomas Jerzak +2
We investigate the potential of large language models (LLMs) to disentangle text variables--to remove the textual traces of an undesired forbidden variable in a task sometimes know…
The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models
Lovisa Hagström, Denitsa Saynova, Tobias Norlund +2
Large Language Models (LLMs) make natural interfaces to factual knowledge, but their usefulness is limited by their tendency to deliver inconsistent answers to semantically equival…