Papers by Rahul Zalkikar
Measuring Social Biases in Masked Language Models by Proxy of Prediction Quality (2025.acl-long)
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| Challenge: | Innovative transformer-based language models produce contextually-aware token embeddings, but have been shown to encode unwanted biases for downstream applications. |
| Approach: | They extend previous work by evaluating social biases introduced after retraining an MLM under the masked language modeling objective and propose proxy functions within an iterative masking experiment to measure the quality of transformer models’ predictions. |
| Outcome: | The proposed proxy functions within an iterative masking experiment show that all transformer models encode concerning social biases. |