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NOURBAKHSH Aria

University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)

Main Referenced Co-authors
SCHOMMER, Christoph  (2)
ALCARAZ, Benoît  (1)
El Mahdaouy, Abdelkader (1)
LAMSIYAH, Salima  (1)
Main Referenced Keywords
Attribution maps, (1); Educational Question Generation · Large Language Model · Google FLAN-T5 · Reinforcement Learning · Self-Critical Sequence Training (1); Feature engineerings (1); Feature Generation (1); Feature generation (1);
Main Referenced Disciplines
Computer science (3)

Publications (total 3)

The most downloaded
3 downloads
NOURBAKHSH, A. (2025). Quantifying the Overlap: Attribution Maps and Linguistic Heuristics in Encoder-Decoder Machine Translation Models [Paper presentation]. RANLP 2025. https://hdl.handle.net/10993/67650

The most cited

8 citations (OpenAlex)

LAMSIYAH, S., El Mahdaouy, A., NOURBAKHSH, A., & SCHOMMER, C. (2024). Fine-Tuning a Large Language Model with Reinforcement Learning for Educational Question Generation. In Lecture Notes in Computer Science. recife, Brazil: Springer Nature Switzerland. doi:10.1007/978-3-031-64302-6_30 https://hdl.handle.net/10993/61779

NOURBAKHSH, A. (2025). Quantifying the Overlap: Attribution Maps and Linguistic Heuristics in Encoder-Decoder Machine Translation Models [Paper presentation]. RANLP 2025.
Peer reviewed

NOURBAKHSH, A., ALCARAZ, B., & SCHOMMER, C. (2025). Feature Generation Using LLMs: An Evolutionary Algorithm Approach. In Y. Mualla (Ed.), Advances in Explainability, Agents, and Large Language Models - 1st International Workshop on Causality, Agents and Large Models, CALM 2024, Proceedings. Springer Science and Business Media Deutschland GmbH. doi:10.1007/978-3-031-89103-8_4
Peer reviewed

LAMSIYAH, S., El Mahdaouy, A., NOURBAKHSH, A., & SCHOMMER, C. (2024). Fine-Tuning a Large Language Model with Reinforcement Learning for Educational Question Generation. In Lecture Notes in Computer Science. recife, Brazil: Springer Nature Switzerland. doi:10.1007/978-3-031-64302-6_30
Peer reviewed

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