Do ever larger octopi still amplify reporting biases? Evidence from judgments of typical colour

@inproceedings{Liu2022DoEL,
  title={Do ever larger octopi still amplify reporting biases? Evidence from judgments of typical colour},
  author={Fangyu Liu and Julian Martin Eisenschlos and Jeremy R. Cole and Nigel Collier},
  booktitle={AACL},
  year={2022}
}
Language models (LMs) trained on raw texts have no direct access to the physical world. Gordon and Van Durme (2013) point out that LMs can thus suffer from reporting bias: texts rarely report on common facts, instead focusing on the unusual aspects of a situation. If LMs are only trained on text corpora and naively memorise local co-occurrence statistics, they thus naturally would learn a biased view of the physical world. While prior studies have repeatedly verified that LMs of smaller scales… 
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