🧑‍🔬 Ethan Fetaya

🏛️ Affiliations

🎓Bar-Ilan UniversityRamat Gan · Israel2018–2026 · 43 papersEmployment since 2019current🏢NvidiaSanta Clara · United States2026 · 1 papercurrent🎓University of TorontoToronto · Canada2017–2019 · 8 papers🎓Weizmann Institute of ScienceRehovot · Israel2014–2016 · 7 papers🔬Vector InstituteToronto · Canada2018–2019 · 3 papers🏢General MotorsDetroit · United States2017–2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Restoration of Fragmentary Babylonian Texts Using Recurrent Neural Networks (2020 · 65 citations)
   Clay tablets from Achaemenid Babylonia are often broken, and experts fill the gaps by hand. The authors collect about 2,250 late Babylonian archival texts (legal, economic and administrative) from an online corpus, tokenise them with a custom Akkadian tokenizer (names, gods, places and months become class tokens…
2. LR-DWM: Efficient Watermarking for Diffusion Language Models (2026)
   Most text watermarks for LLMs assume autoregressive decoding, where each token is biased using the tokens already produced to its left.

All works

9 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. Neural Relational Inference for Interacting Systems ↗UvA-DARE (University of Amsterdam) · no summary yetThomas Kipf et al.2018 · 281 citations
2. Inference in Probabilistic Graphical Models by Graph Neural Networks ↗2018 52nd Asilomar Conference on Signals, Systems, and Computers · no summary yetKijung Yoon et al.2018 · 82 citations
3. Restoration of Fragmentary Babylonian Texts Using Recurrent Neural NetworksEthan Fetaya, Yonatan Lifshitz, Elad Aaron, et al.Semitic languages · 65 citations
4. Reviving and Improving Recurrent Back-Propagation ↗arXiv (Cornell University) · no summary yetRenjie Liao et al.2018 · 33 citations
5. Incremental Few-Shot Learning with Attention Attractor Networks ↗arXiv (Cornell University) · no summary yetMengye Ren et al.2018 · 33 citations
6. Neural Guided Constraint Logic Programming for Program Synthesis ↗arXiv (Cornell University) · no summary yetLisa Zhang et al.2018 · 17 citations
7. Understanding the Limitations of Conditional Generative Models ↗arXiv (Cornell University) · no summary yetEthan Fetaya et al.2019 · 15 citations
8. Leveraging Constraint Logic Programming for Neural Guided Program Synthesis. ↗International Conference on Learning Representations · no summary yetLisa Zhang et al.2018 · 6 citations
9. LR-DWM: Efficient Watermarking for Diffusion Language ModelsFindings of the Association for Computational LinguisticsOfek Raban, Gal Chechik, Ethan Fetaya2026

🤝 Co-authors here

1 co-author with a page, the most papers together first.

• Shai Gordin

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• 2018 52nd Asilomar Conference on Signals, Systems, and Computers
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
• Proceedings of the National Academy of Sciences: Proceedings of the National Academy of Sciences 2020
• International Conference on Learning Representations
• UvA-DARE (University of Amsterdam)

🔗 Cited by

Papers of our library cite their works 89 times (of the 149,439 papers whose bibliographies we read); 9 citing papers with a page here →.

Updated 1 November 2026

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