Rexhina Blloshmi

According to our database1, Rexhina Blloshmi authored at least 11 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2023
LI-RAGE: Late Interaction Retrieval Augmented Generation with Explicit Signals for Open-Domain Table Question Answering.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

An Inner Table Retriever for Robust Table Question Answering.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
From shallow to whole-sentence semantics: semantic parsing in English and beyond.
PhD thesis, 2022

Evaluating Multilingual Sentence Representation Models in a Real Case Scenario.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

STEPS: Semantic Typing of Event Processes with a Sequence-to-Sequence Approach.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

BabelNet Meaning Representation: A Fully Semantic Formalism to Overcome Language Barriers.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Generating Senses and RoLes: An End-to-End Model for Dependency- and Span-based Semantic Role Labeling.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

IR like a SIR: Sense-enhanced Information Retrieval for Multiple Languages.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

SPRING Goes Online: End-to-End AMR Parsing and Generation.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2021

One SPRING to Rule Them Both: Symmetric AMR Semantic Parsing and Generation without a Complex Pipeline.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
XL-AMR: Enabling Cross-Lingual AMR Parsing with Transfer Learning Techniques.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020


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