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Found 4 papers, 1 papers with code
Undesirable Biases in NLP: Addressing Challenges of Measurement
In particular, we will explore two central notions from psychometrics, the construct validity and the reliability of measurement tools, and discuss how they can be applied in the context of measuring model bias.
The Birth of Bias: A case study on the evolution of gender bias in an English language model
With full access to the data and to the model parameters as they change during every step while training, we can map in detail how the representation of gender develops, what patterns in the dataset drive this, and how the model's internal state relates to the bias in a downstream task (semantic textual similarity).
Observing Interventions: A logic for thinking about experiments
Therefore, in a second step, we implement a more complex notion of knowledge that allows an agent to observe (measure) certain variables when an experiment is carried out.
Thinking About Causation: A Causal Language with Epistemic Operators
To this purpose, we extend the notion of a causal model with a representation of the epistemic state of an agent.
