Papers by Sitiporn Sae Lim
Identifying and Mitigating Annotation Bias in Natural Language Understanding using Causal Mediation Analysis (2024.findings-acl)
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Sitiporn Sae Lim, Can Udomcharoenchaikit, Peerat Limkonchotiwat, Ekapol Chuangsuwanich, Sarana Nutanong
| Challenge: | Current NLU models obtain state-of-the-art accuracy on in-distribution benchmarks, but they use annotation bias to make predictions, negatively affecting the models' generalizability. |
| Approach: | They apply causal mediation analysis to gauge how much each component mediates annotation biases and use causal-grounded masking and gradient unlearning to mitigate bias. |
| Outcome: | The proposed methods improve the model's robustness against annotation bias even after employing other training-time debiasing techniques. |