no code implementations • ACL (spnlp) 2021 • Erenay Dayanik, Andre Blessing, Nico Blokker, Sebastian Haunss, Jonas Kuhn, Gabriella Lapesa, Sebastian Padó
The analysis of public debates crucially requires the classification of political demands according to hierarchical claim ontologies (e. g. for immigration, a supercategory “Controlling Migration” might have subcategories “Asylum limit” or “Border installations”).
no code implementations • EACL (WASSA) 2021 • Erenay Dayanik, Sebastian Padó
Text classification is a central tool in NLP.
no code implementations • EMNLP (NLP+CSS) 2020 • Nico Blokker, Erenay Dayanik, Gabriella Lapesa, Sebastian Padó
Manifestos are official documents of political parties, providing a comprehensive topical overview of the electoral programs.
1 code implementation • IWCS (ACL) 2021 • Touhidul Alam, Alessandra Zarcone, Sebastian Padó
Reliable tagging of Temporal Expressions (TEs, e. g., Book a table at L’Osteria for Sunday evening) is a central requirement for Voice Assistants (VAs).
1 code implementation • 19 Mar 2024 • Dojun Park, Sebastian Padó
Almost all frameworks for the manual or automatic evaluation of machine translation characterize the quality of an MT output with a single number.
no code implementations • 18 Mar 2024 • Sungjun Han, Sebastian Padó
This indicates the usefulness of in-context learning problems as an inductive bias for generalization.
no code implementations • 27 Feb 2024 • Tanise Ceron, Neele Falk, Ana Barić, Dmitry Nikolaev, Sebastian Padó
Due to the widespread use of large language models (LLMs) in ubiquitous systems, we need to understand whether they embed a specific worldview and what these views reflect.
no code implementations • 5 Feb 2024 • Lucas Möller, Dmitry Nikolaev, Sebastian Padó
In this work, we reassess these restrictions and propose (i) a model with exact attribution ability that retains the original model's predictive performance and (ii) a way to compute approximate attributions for off-the-shelf models.
no code implementations • 1 Feb 2024 • Ana Barić, Sean Papay, Sebastian Padó
The identification of political actors who put forward claims in public debate is a crucial step in the construction of discourse networks, which are helpful to analyze societal debates.
1 code implementation • 19 Oct 2023 • Dmitry Nikolaev, Tanise Ceron, Sebastian Padó
We carry out the analysis of the Comparative Manifestos Project dataset across 41 countries and 27 languages and find that the task can be efficiently solved by state-of-the-art models, with label aggregation producing the best results.
1 code implementation • 18 Oct 2023 • Dmitry Nikolaev, Sebastian Padó
The question of what kinds of linguistic information are encoded in different layers of Transformer-based language models is of considerable interest for the NLP community.
no code implementations • 13 Oct 2023 • Urs Zaberer, Sebastian Padó, Gabriella Lapesa
The identification and classification of political claims is an important step in the analysis of political newspaper reports; however, resources for this task are few and far between.
1 code implementation • 9 Oct 2023 • Lucas Möller, Dmitry Nikolaev, Sebastian Padó
Despite the success of Siamese encoder models such as sentence transformers (ST), little is known about the aspects of inputs they pay attention to.
no code implementations • 31 May 2023 • Dmitry Nikolaev, Collin F. Baker, Miriam R. L. Petruck, Sebastian Padó
This paper begins with the premise that adverbs are neglected in computational linguistics.
1 code implementation • 17 May 2023 • Tanise Ceron, Dmitry Nikolaev, Sebastian Padó
The workflow covers (a) definition of suitable policy domains; (b) automatic labeling of domains, if no manual labels are available; (c) computation of domain-level similarities and aggregation at a global level; (d) extraction of interpretable party positions on major policy axes via multidimensional scaling.
no code implementations • 30 Jan 2023 • Dmitry Nikolaev, Sebastian Padó
Variants of the BERT architecture specialised for producing full-sentence representations often achieve better performance on downstream tasks than sentence embeddings extracted from vanilla BERT.
1 code implementation • 21 Oct 2022 • Tanise Ceron, Nico Blokker, Sebastian Padó
Even though fine-tuned neural language models have been pivotal in enabling "deep" automatic text analysis, optimizing text representations for specific applications remains a crucial bottleneck.
no code implementations • 29 Jul 2022 • Lucas Möller, Sebastian Padó
A number of models for neural content-based news recommendation have been proposed.
no code implementations • NAACL (SIGTYP) 2022 • Dmitry Nikolaev, Sebastian Padó
The capabilities and limitations of BERT and similar models are still unclear when it comes to learning syntactic abstractions, in particular across languages.
no code implementations • 20 Jan 2022 • Moiz Rauf, Sebastian Padó, Michael Pradel
Source code summarization is the task of generating a high-level natural language description for a segment of programming language code.
no code implementations • 19 Nov 2021 • Nico Blokker, André Blessing, Erenay Dayanik, Jonas Kuhn, Sebastian Padó, Gabriella Lapesa
Besides the released resources and the case-study, our contribution is also methodological: we talk the reader through the steps from a newspaper article to a discourse network, demonstrating that there is not just one discourse network for the German migration debate, but multiple ones, depending on the topic of interest (political actors, policy fields, time spans).
no code implementations • 21 Sep 2021 • Flor Miriam Plaza-del-Arco, Sercan Halat, Sebastian Padó, Roman Klinger
The recognition of hate speech and offensive language (HOF) is commonly formulated as a classification task to decide if a text contains HOF.
1 code implementation • ICLR 2022 • Sean Papay, Roman Klinger, Sebastian Padó
However, the CRF's Markov assumption makes it impossible for CRFs to represent distributions with \textit{nonlocal} dependencies, and standard CRFs are unable to respect nonlocal constraints of the data (such as global arity constraints on output labels).
Ranked #6 on Semantic Role Labeling on OntoNotes
no code implementations • EACL (WASSA) 2021 • Enrica Troiano, Sebastian Padó, Roman Klinger
When humans judge the affective content of texts, they also implicitly assess the correctness of such judgment, that is, their confidence.
no code implementations • EMNLP 2020 • Sean Papay, Roman Klinger, Sebastian Padó
Span identification (in short, span ID) tasks such as chunking, NER, or code-switching detection, ask models to identify and classify relevant spans in a text.
no code implementations • 23 Nov 2019 • Iris Hendrickx, Su Nam Kim, Zornitsa Kozareva, Preslav Nakov, Diarmuid Ó Séaghdha, Sebastian Padó, Marco Pennacchiotti, Lorenza Romano, Stan Szpakowicz
In this paper, we define the task, describe the creation of the datasets, and discuss the results of the participating 28 systems submitted by 10 teams.
no code implementations • ACL 2019 • Enrica Troiano, Sebastian Padó, Roman Klinger
Sentiment analysis has a range of corpora available across multiple languages.
no code implementations • Thirty-Second AAAI Conference on Artificial Intelligence 2018 • Domagoj Alagić, Jan Šnajder, Sebastian Padó
Word sense induction is the most prominent unsupervised approach to lexical disambiguation.
no code implementations • 6 Feb 2017 • Gemma Boleda, Sebastian Padó, Nghia The Pham, Marco Baroni
Reference is a crucial property of language that allows us to connect linguistic expressions to the world.
no code implementations • 28 Jun 2016 • Gemma Boleda, Sebastian Padó, Marco Baroni
One of the most basic functions of language is to refer to objects in a shared scene.