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Found 5 papers, 2 papers with code
Exploring the Use of Foundation Models for Named Entity Recognition and Lemmatization Tasks in Slavic Languages
This paper describes Adam Mickiewicz University's (AMU) solution for the 4th Shared Task on SlavNER.
Adam Mickiewicz University at WMT 2022: NER-Assisted and Quality-Aware Neural Machine Translation
One of the models in the ensemble is a document-level model, trained on parallel and synthetic longer sequences.
STable: Table Generation Framework for Encoder-Decoder Models
The output structure of database-like tables, consisting of values structured in horizontal rows and vertical columns identifiable by name, can cover a wide range of NLP tasks.
Joint Entity and Relation Extraction
Knowledge Base Population
Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer
We address the challenging problem of Natural Language Comprehension beyond plain-text documents by introducing the TILT neural network architecture which simultaneously learns layout information, visual features, and textual semantics.
Ranked #7 on
Visual Question Answering (VQA)
on InfographicVQA
(using extra training data)
Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines
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, given a few examples of similar clauses from other legal acts.
Ranked #1 on
Semantic Retrieval
on Contract Discovery
