Language modelling ’ s generative model : is it rational ?

By Karen Spärck. 2004

Subfields: Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Angelina McMillan-Major
2. Timnit Gebru
3. Iason Gabriel
4. John F. J. Mellor
5. Borja Balle
6. Geoffrey Irving
7. Amelia Glaese
8. Myra Cheng

Citations in the corpus

• Ethical and social risks of harm from Language Models (2021, background): “It follows from the above that scaling up LM size will be insufficient for fully resolving the problem of LMs assigning high probabilities to false information (Bender and Koller, 2020; Lin et al., 2021; Sabeti, 2020; Sparck Jones, 2004).”
• Taxonomy of Risks posed by Language Models (2022, background): “likely be insufficient for resolving the problem of LMs generating factually incorrect statements [16, 118, 148, 172].”
• On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 (2021, background): “As the late Karen Spärck Jones pointed out: the use of LMs ties us to certain (usually unstated) epistemological and methodological commitments [124].”