Papers by Piotr Andruszkiewicz
Annotated Corpus of Scientific Conference’s Homepages for Information Extraction (L18-1)
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| Challenge: | a corpus of scientific conferences contains homepages with annotations of important information . name of conference, abbreviation, place, submission, notification, camera ready dates are included . |
| Approach: | They propose a corpus that contains 943 homepages of scientific conferences with annotations of interesting information. |
| Outcome: | The proposed corpus contains 943 homepages of scientific conferences, 14794 including subpages . the results show that it can be used as a reference data set for this type of task. |
No Train but Gain: Language Arithmetic for training-free Language Adapters enhancement (2025.coling-main)
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| Challenge: | Modular deep learning is the most effective way to lift the curse of multilinguality. |
| Approach: | They propose a method which enables training-free post-processing to address this limitation by adding learning to the language adapters and transitioning the framework from a multi-task to a multiple language setup. |
| Outcome: | The proposed method consistently improves baselines with significant gains, especially in the most challenging case of zero-shot application. |
Is Modularity Transferable? A Case Study through the Lens of Knowledge Distillation (2024.lrec-main)
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| Challenge: | Existing approaches to modularity are limited to the case of pre-trained modules in a pre-training language model. |
| Approach: | They propose a method that allows the transfer of pre-trained PEFT modules between incompatible PLMs without any change in the inference complexity. |
| Outcome: | The proposed method allows the transfer of modules between incompatible PLMs without any change in the inference complexity. |
Is a Document Educational or Just Wikipedia-Style? — Pitfalls of Classifier-Based Quality Filtering (2026.acl-short)
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| Challenge: | Large Language Models (LLMs) are pre-trained on massive data corpora, and the quality of these corporales is one of the main factors in achieving stateof-the-art performance. |
| Approach: | They propose to use Wikipedia-style reformatting to alter a model's quality assessment and enable low-quality content to surpass filtering thresholds. |
| Outcome: | The proposed model would reverse filtering decision for approximately 7% of evaluated documents, thereby admitting content into the pre-training corpus that would otherwise have been excluded. |
Multilingual Entity and Relation Extraction Dataset and Model (2021.eacl-main)
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| Challenge: | HERBERTa is a pipeline for a multilingual task involving two separate BERT models. |
| Approach: | They propose a dataset and a model that combines two independently pretrained BERT models for a multilingual setting to approach the task of Joint Entity and Relation Extraction. |
| Outcome: | The proposed dataset achieves micro F1 81.49 for English on the SMiLER dataset . the proposed pipeline is close to the current SOTA on CoNLL, SpERT . |