22 citations · 36 across the 9 of their papers we have counts for
12 papers
Seamlessly Integrating Tree-Based Positional Embeddings into Transformer Models for Source Code Representation
Patryk Bartkowiak, Filip Graliński
Transformer-based models have demonstrated significant success in various source code representation tasks. Nonetheless, traditional positional embeddings employed by these models…
Tackling prediction tasks in relational databases with LLMs
Marek Wydmuch, Łukasz Borchmann, Filip Graliński
Though large language models (LLMs) have demonstrated exceptional performance across numerous problems, their application to predictive tasks in relational databases remains largel…
CCpdf: Building a High Quality Corpus for Visually Rich Documents from Web Crawl Data
Michał Turski, Tomasz Stanisławek, Karol Kaczmarek +2
In recent years, the field of document understanding has progressed a lot. A significant part of this progress has been possible thanks to the use of language models pretrained on…
Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts
Tomasz Stanisławek, Filip Graliński, Anna Wróblewska +5
The relevance of the Key Information Extraction (KIE) task is increasingly important in natural language processing problems. But there are still only a few well-defined problems t…
From Dataset Recycling to Multi-Property Extraction and Beyond
Tomasz Dwojak, Michał Pietruszka, Łukasz Borchmann +2
This paper investigates various Transformer architectures on the WikiReading Information Extraction and Machine Reading Comprehension dataset. The proposed dual-source model outper…
Successive Halving Top-k Operator
Michał Pietruszka, Łukasz Borchmann, Filip Graliński
We propose a differentiable successive halving method of relaxing the top-k operator, rendering gradient-based optimization possible. The need to perform softmax iteratively on the…
Dynamic Boundary Time Warping for Sub-sequence Matching with Few Examples
Łukasz Borchmann, Dawid Jurkiewicz, Filip Graliński +1
The paper presents a novel method of finding a fragment in a long temporal sequence similar to the set of shorter sequences. We are the first to propose an algorithm for such a sea…
On the Multi-Property Extraction and Beyond
Tomasz Dwojak, Michał Pietruszka, Łukasz Borchmann +2
In this paper, we investigate the Dual-source Transformer architecture on the WikiReading information extraction and machine reading comprehension dataset. The proposed model outpe…
ApplicaAI at SemEval-2020 Task 11: On RoBERTa-CRF, Span CLS and Whether Self-Training Helps Them
Dawid Jurkiewicz, Łukasz Borchmann, Izabela Kosmala +1
This paper presents the winning system for the propaganda Technique Classification (TC) task and the second-placed system for the propaganda Span Identification (SI) task. The purp…
Kleister: A novel task for Information Extraction involving Long Documents with Complex Layout
Filip Graliński, Tomasz Stanisławek, Anna Wróblewska +5
State-of-the-art solutions for Natural Language Processing (NLP) are able to capture a broad range of contexts, like the sentence-level context or document-level context for short…
LAMBERT: Layout-Aware (Language) Modeling for information extraction
Łukasz Garncarek, Rafał Powalski, Tomasz Stanisławek +4
We introduce a simple new approach to the problem of understanding documents where non-trivial layout influences the local semantics. To this end, we modify the Transformer encoder…
Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines
Łukasz Borchmann, Dawid Wiśniewski, Andrzej Gretkowski +7
We propose a new shared task of semantic retrieval from legal texts, in which a so-called contract discovery is to be performed, where legal clauses are extracted from documents, g…