Papers by Polina Zablotskaia
“Will You Find These Shortcuts?” A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classification (2022.emnlp-main)
Copied to clipboard
| Challenge: | Existing work on faithfulness evaluation is not conclusive and does not provide a clear answer as to how different methods are to be compared. |
| Approach: | They propose a protocol for faithfulness evaluation that makes use of partially synthetic data to obtain ground truth for feature importance ranking. |
| Outcome: | The proposed method is based on partially synthetic data and is compared with lexical shortcuts on a range of datasets and LSTM models. |
On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Modern deep models for summarization generate miscalibrated predictive uncertainty, compromising reliability and trustworthiness in real-world applications. |
| Approach: | They propose to use probabilistic methods to improve the uncertainty quality of neural summarization models by using three large-scale benchmarks with varying difficulty. |
| Outcome: | The proposed methods consistently improve the model’s generation and uncertainty quality, leading to improved selective generation performance (i.e., abstaining from low-quality summaries) in practice. |