🧑‍🔬 Douglas Eck

🏛️ Affiliations

🏢GoogleMountain View · United States2011–2022 · 29 papers🎓Université de MontréalMontreal · Canada2005–2011 · 28 papers🔬Dalle Molle Institute for Artificial Intelligence ResearchLugano · Switzerland2001–2004 · 12 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions 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

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Automatic Detection of Generated Text is Easiest when Humans are Fooled (2019 · 411 citations)
   The paper asks why people and automatic classifiers disagree about whether a text came from a person or a language model, and how the decoding strategy shapes that gap.
2. A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis (2023 · 120 citations)
   Agents driven by large language models do well on simulated web environments but struggle on real websites.

All works

13 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. Gemma: Open Models Based on Gemini Research and Technology ↗arXiv:2403.08295 · no summary yetGemma Team et al.2024 · 1,313 citations
2. Deduplicating Training Data Makes Language Models Better ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetKatherine Lee et al.2022 · 623 citations
3. Automatic Detection of Generated Text is Easiest when Humans are FooledAnnual Meeting of the Association for Computational Linguistics (ACL)Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, et al.2019 · 411 citations
4. Music Transformer: Generating Music with Long-Term Structure ↗International Conference on Learning Representations · no summary yetCheng-Zhi Anna Huang et al.2019 · 314 citations
5. A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music ↗arXiv (Cornell University) · no summary yetRoberts, Adam et al.2018 · 296 citations
6. Online and Linear-Time Attention by Enforcing Monotonic Alignments ↗arXiv (Cornell University) · no summary yetColin Raffel et al.2017 · 267 citations
7. A Real-World WebAgent with Planning, Long Context Understanding, and Program SynthesisarXiv:2307.12856Izzeddin Gur, Hiroki Furuta, Austin Huang, et al.2023 · 120 citations
8. Music Transformer ↗arXiv (Cornell University) · no summary yetCheng-Zhi Anna Huang et al.2018 · 117 citations
9. Biologically Plausible Speech Recognition with LSTM Neural Nets ↗Lecture notes in computer science · no summary yetAlex Graves et al.2004 · 105 citations
10. Onsets and Frames: Dual-Objective Piano Transcription ↗arXiv (Cornell University) · no summary yetCurtis Hawthorne et al.2017 · 47 citations
11. Learning a Latent Space of Multitrack Measures ↗arXiv (Cornell University) · no summary yetIan Simon et al.2018 · 29 citations
12. Visualizing Music Self-Attention ↗no summary yetAnna Huang et al.2018 · 3 citations
13. Comparing LSTM Recurrent Networks with Spiking Recurrent Networks on the Recognition of Spoken Digits. ↗no summary yetAlex Graves, Douglas Eck, Jürgen Schmidhuber2003

🤝 Co-authors here

7 co-authors with a page, the most papers together first.

• Aleksandra Faust
• Chris Callison-Burch
• Daniel Duckworth
• Daphne Ippolito
• Hiroki Furuta
• Mustafa Safdari
• Yutaka Matsuo

Venues

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

• Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2019
• International Conference on Learning Representations
• Lecture notes in computer science

🔗 Cited by

Papers of our library cite their works 4,540 times (of the 149,439 papers whose bibliographies we read); 1,072 citing papers with a page here →.

Updated 2 November 2026

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