Papers by Piotr Piękos
PDR: A Plug-and-Play Positional Decay Framework for LLM Pre-training Data Detection (2026.acl-long)
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| Challenge: | Existing likelihood-based methods for detecting pretraining data are limited in black-box, zero-shot settings. |
| Approach: | They propose a training-free and plug-and-play framework that reweights token-level scores to amplify distinct signals from early positions while suppressing noise from later ones. |
| Outcome: | The proposed framework amplifys signals from early positions while suppressing noise from later positions. |
Measuring and Improving BERT’s Mathematical Abilities by Predicting the Order of Reasoning. (2021.acl-short)
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| Challenge: | a common language model for word math problems lacks mathematical abilities . a data-driven approach to solving word problems is lacking in many areas . |
| Approach: | They propose to train a language model with mathematical abilities to teach word maths . they propose to use semi-formal steps to explain how math results are derived . |
| Outcome: | The proposed model achieves better outcomes than baseline models and on-par with more tailored models. |