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2020 – today
- 2024
[c25]Alberto Barrón-Cedeño
, Firoj Alam, Julia Maria Struß, Preslav Nakov, Tanmoy Chakraborty, Tamer Elsayed, Piotr Przybyla, Tommaso Caselli, Giovanni Da San Martino, Fatima Haouari, Maram Hasanain, Chengkai Li, Jakub Piskorski, Federico Ruggeri, Xingyi Song, Reem Suwaileh:
Overview of the CLEF-2024 CheckThat! Lab: Check-Worthiness, Subjectivity, Persuasion, Roles, Authorities, and Adversarial Robustness. CLEF (2) 2024: 28-52- [c24]Piotr Przybyla, Ben Wu, Alexander V. Shvets, Yida Mu, Kim Cheng Sheang, Xingyi Song, Horacio Saggion:
Overview of the CLEF-2024 CheckThat! Lab Task 6 on Robustness of Credibility Assessment with Adversarial Examples (InCrediblAE). CLEF (Working Notes) 2024: 321-338 - [c23]Piotr Rybak, Piotr Przybyla, Maciej Ogrodniczuk:
PolQA: Polish Question Answering Dataset. LREC/COLING 2024: 12846-12855 - [c22]Alberto Barrón-Cedeño, Firoj Alam, Tanmoy Chakraborty, Tamer Elsayed, Preslav Nakov, Piotr Przybyla, Julia Maria Struß, Fatima Haouari, Maram Hasanain, Federico Ruggeri, Xingyi Song, Reem Suwaileh:
The CLEF-2024 CheckThat! Lab: Check-Worthiness, Subjectivity, Persuasion, Roles, Authorities, and Adversarial Robustness. ECIR (5) 2024: 449-458 - [c21]Piotr Przybyla, Euan McGill, Horacio Saggion:
Know Thine Enemy: Adaptive Attacks on Misinformation Detection Using Reinforcement Learning. WASSA 2024: 125-140 - [c20]Igor Kuzmin, Piotr Przybyla, Euan McGill, Horacio Saggion:
TRIBBLE - TRanslating IBerian languages Based on Limited E-resources. WMT 2024: 955-959 - [i7]Piotr Przybyla:
Attacking Misinformation Detection Using Adversarial Examples Generated by Language Models. CoRR abs/2410.20940 (2024) - 2023
- [c19]Lukasz Kobylinski, Maciej Ogrodniczuk, Piotr Rybak, Piotr Przybyla, Piotr Pezik, Agnieszka Mikolajczyk, Wojciech Janowski, Michal Marcinczuk, Aleksander Smywinski-Pohl:
PolEval 2022/23 Challenge Tasks and Results. FedCSIS 2023: 1243-1250 - [c18]Piotr Przybyla, Konrad Kaczynski:
Where Does It End? Long Named Entity Recognition for Propaganda Detection and Beyond. NLP-MisInfo@SEPLN 2023: 18-35 - [c17]Piotr Przybyla, Horacio Saggion:
ERINIA: Evaluating the Robustness of Non-Credible Text Identification by Anticipating Adversarial Actions. NLP-MisInfo@SEPLN 2023: 45-52 - [c16]Piotr Przybyla, Nicolau Duran-Silva, Santiago Egea Gómez:
I've Seen Things You Machines Wouldn't Believe: Measuring Content Predictability to Identify Automatically-Generated Text. IberLEF@SEPLN 2023 - [i6]Piotr Przybyla, Alexander V. Shvets, Horacio Saggion:
BODEGA: Benchmark for Adversarial Example Generation in Credibility Assessment. CoRR abs/2303.08032 (2023) - 2022
- [c15]Piotr Przybyla, Matthew Shardlow:
Using NLP to quantify the environmental cost and diversity benefits of in-person NLP conferences. ACL (Findings) 2022: 3853-3863 - [c14]Piotr Przybyla, Piotr Borkowski, Konrad Kaczynski:
Countering Disinformation by Finding Reliable Sources: a Citation-Based Approach. IJCNN 2022: 1-8 - [i5]Matthew Shardlow, Piotr Przybyla:
Deanthropomorphising NLP: Can a Language Model Be Conscious? CoRR abs/2211.11483 (2022) - [i4]Piotr Rybak, Piotr Przybyla, Maciej Ogrodniczuk:
Improving Question Answering Performance through Manual Annotation: Costs, Benefits and Strategies. CoRR abs/2212.08897 (2022) - 2021
- [j8]Piotr Przybyla, Axel J. Soto:
When classification accuracy is not enough: Explaining news credibility assessment. Inf. Process. Manag. 58(5): 102653 (2021) - [c13]Laura Vásquez-Rodríguez, Matthew Shardlow, Piotr Przybyla, Sophia Ananiadou:
Investigating Text Simplification Evaluation. ACL/IJCNLP (Findings) 2021: 876-882 - [c12]Konrad Kaczynski, Piotr Przybyla:
HOMADOS at SemEval-2021 Task 6: Multi-Task Learning for Propaganda Detection. SemEval@ACL/IJCNLP 2021: 1027-1031 - [c11]Laura Vásquez-Rodríguez, Matthew Shardlow, Piotr Przybyla, Sophia Ananiadou:
The Role of Text Simplification Operations in Evaluation. CTTS@SEPLN 2021 - [i3]Laura Vásquez-Rodríguez, Matthew Shardlow, Piotr Przybyla, Sophia Ananiadou:
Investigating Text Simplification Evaluation. CoRR abs/2107.13662 (2021) - 2020
- [c10]Piotr Przybyla:
Capturing the Style of Fake News. AAAI 2020: 490-497 - [c9]Piotr Przybyla, Matthew Shardlow:
Multi-Word Lexical Simplification. COLING 2020: 1435-1446
2010 – 2019
- 2019
- [j7]Axel J. Soto, Piotr Przybyla, Sophia Ananiadou:
Thalia: semantic search engine for biomedical abstracts. Bioinform. 35(10): 1799-1801 (2019) - [j6]Piotr Przybyla, Austin J. Brockmeier, Sophia Ananiadou:
Quantifying risk factors in medical reports with a context-aware linear model. J. Am. Medical Informatics Assoc. 26(6): 537-546 (2019) - [j5]Austin J. Brockmeier, Meizhi Ju, Piotr Przybyla, Sophia Ananiadou:
Improving reference prioritisation with PICO recognition. BMC Medical Informatics Decis. Mak. 19(1): 256 (2019) - [c8]Jakub Gasior, Piotr Przybyla:
The IPIPAN Team Participation in the Check-Worthiness Task of the CLEF2019 CheckThat! Lab. CLEF (Working Notes) 2019 - [c7]Piotr Przybyla:
Detecting Bot Accounts on Twitter by Measuring Message Predictability. CLEF (Working Notes) 2019 - 2017
- [j4]Georgios Kontonatsios, Austin J. Brockmeier, Piotr Przybyla, John McNaught, Tingting Mu, John Yannis Goulermas, Sophia Ananiadou:
A semi-supervised approach using label propagation to support citation screening. J. Biomed. Informatics 72: 67-76 (2017) - [c6]Piotr Przybyla, Axel J. Soto, Sophia Ananiadou:
Identifying Personalised Treatments and Clinical Trials for Precision Medicine using Semantic Search with Thalia. TREC 2017 - [i2]Piotr Przybyla:
How big is big enough? Unsupervised word sense disambiguation using a very large corpus. CoRR abs/1710.07960 (2017) - 2016
- [j3]Piotr Przybyla, Matthew Shardlow, Sophie Aubin, Robert Bossy, Richard Eckart de Castilho, Stelios Piperidis, John McNaught, Sophia Ananiadou:
Text mining resources for the life sciences. Database J. Biol. Databases Curation 2016 (2016) - [c5]Piotr Przybyla, Nhung T. H. Nguyen, Matthew Shardlow, Georgios Kontonatsios, Sophia Ananiadou:
NaCTeM at SemEval-2016 Task 1: Inferring sentence-level semantic similarity from an ensemble of complementary lexical and sentence-level features. SemEval@NAACL-HLT 2016: 614-620 - [i1]Piotr Przybyla:
Boosting Question Answering by Deep Entity Recognition. CoRR abs/1605.08675 (2016) - 2015
- [c4]Piotr Przybyla, Pawel Teisseyre:
What Do Your Look-alikes Say about You? Exploiting Strong and Weak Similarities for Author Profiling. CLEF (Working Notes) 2015 - [c3]Piotr Przybyla:
Gathering Knowledge for Question Answering Beyond Named Entities. NLDB 2015: 412-417 - 2014
- [j2]Piotr Przybyla, Katarzyna Sznajd-Weron, Rafal Weron:
Diffusion of Innovation within an Agent-Based Model: Spinsons, Independence and Advertising. Adv. Complex Syst. 17(1) (2014) - [j1]Piotr Przybyla, Pawel Teisseyre:
Analysing Utterances in Polish Parliament to Predict Speaker's Background. J. Quant. Linguistics 21(4): 350-376 (2014) - 2013
- [c2]Piotr Przybyla:
Question Analysis for Polish Question Answering. ACL (Student Research Workshop) 2013: 96-102 - [c1]Piotr Przybyla:
Question Classification for Polish Question Answering. IIS 2013: 50-56
Coauthor Index
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last updated on 2024-12-10 20:50 CET by the dblp team
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