Search Results for author: Ronald Cardenas

Found 9 papers, 4 papers with code

'Don't Get Too Technical with Me': A Discourse Structure-Based Framework for Science Journalism

1 code implementation23 Oct 2023 Ronald Cardenas, Bingsheng Yao, Dakuo Wang, Yufang Hou

Science journalism refers to the task of reporting technical findings of a scientific paper as a less technical news article to the general public audience.

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code

no code implementations22 Jun 2022 Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran, Alex Wang, Alexandros Papangelis, Aman Madaan, Angelina McMillan-Major, Anna Shvets, Ashish Upadhyay, Bingsheng Yao, Bryan Wilie, Chandra Bhagavatula, Chaobin You, Craig Thomson, Cristina Garbacea, Dakuo Wang, Daniel Deutsch, Deyi Xiong, Di Jin, Dimitra Gkatzia, Dragomir Radev, Elizabeth Clark, Esin Durmus, Faisal Ladhak, Filip Ginter, Genta Indra Winata, Hendrik Strobelt, Hiroaki Hayashi, Jekaterina Novikova, Jenna Kanerva, Jenny Chim, Jiawei Zhou, Jordan Clive, Joshua Maynez, João Sedoc, Juraj Juraska, Kaustubh Dhole, Khyathi Raghavi Chandu, Laura Perez-Beltrachini, Leonardo F. R. Ribeiro, Lewis Tunstall, Li Zhang, Mahima Pushkarna, Mathias Creutz, Michael White, Mihir Sanjay Kale, Moussa Kamal Eddine, Nico Daheim, Nishant Subramani, Ondrej Dusek, Paul Pu Liang, Pawan Sasanka Ammanamanchi, Qi Zhu, Ratish Puduppully, Reno Kriz, Rifat Shahriyar, Ronald Cardenas, Saad Mahamood, Salomey Osei, Samuel Cahyawijaya, Sanja Štajner, Sebastien Montella, Shailza, Shailza Jolly, Simon Mille, Tahmid Hasan, Tianhao Shen, Tosin Adewumi, Vikas Raunak, Vipul Raheja, Vitaly Nikolaev, Vivian Tsai, Yacine Jernite, Ying Xu, Yisi Sang, Yixin Liu, Yufang Hou

This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims.

Benchmarking Text Generation

On the Trade-off between Redundancy and Local Coherence in Summarization

1 code implementation20 May 2022 Ronald Cardenas, Matthias Galle, Shay B. Cohen

Extractive summarization systems are known to produce poorly coherent and, if not accounted for, highly redundant text.

Extractive Summarization Reading Comprehension +1

Unsupervised Extractive Summarization by Human Memory Simulation

no code implementations16 Apr 2021 Ronald Cardenas, Matthias Galle, Shay B. Cohen

We introduce a wide range of heuristics that leverage cognitive representations of content units and how these are retained or forgotten in human memory.

Extractive Summarization Unsupervised Extractive Summarization

CUNI--Malta system at SIGMORPHON 2019 Shared Task on Morphological Analysis and Lemmatization in context: Operation-based word formation

no code implementations WS 2019 Ronald Cardenas, Claudia Borg, Daniel Zeman

This paper presents the submission by the Charles University-University of Malta team to the SIGMORPHON 2019 Shared Task on Morphological Analysis and Lemmatization in context.

Lemmatization Morphological Analysis +1

A Grounded Unsupervised Universal Part-of-Speech Tagger for Low-Resource Languages

1 code implementation NAACL 2019 Ronald Cardenas, Ying Lin, Heng Ji, Jonathan May

We also show extrinsically that incorporating our POS tagger into a name tagger leads to state-of-the-art tagging performance in Sinhalese and Kinyarwanda, two languages with nearly no labeled POS data available.

Clustering Decipherment +4

A Morphological Analyzer for Shipibo-Konibo

no code implementations WS 2018 Ronald Cardenas, Daniel Zeman

We present a fairly complete morphological analyzer for Shipibo-Konibo, a low-resourced native language spoken in the Amazonian region of Peru.

Lemmatization Machine Translation +1

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