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Heinrich Küttler

Heinrich Küttler has 2 papers in our library, in 2020–2021, most of them on Information retrieval & search; often with Aleksandra Piktus, Patrick Lewis, Sebastian Riedel.

2 papers in our library · 2020–2021

OpenAlex · h-index 12 · 19 works · 4,278 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 3,530 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #513

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢MetaMenlo Park · United States2019–2021 · 4 papers🎓Ludwig-Maximilians-Universität MünchenMunich · Germany2011–2014 · 3 papers🏢MetaTel Aviv · Israel2020–2021 · 2 papers🏢MetaLondon · United Kingdom2019–2020 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 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.

📚 Shelves 9The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksEngineering · 1 workSafety Research · 1 workSafety, Risk, Reliability and Quality · 1 workSocial Sciences · 1 workArts and Humanities · 1 workInformation Systems · 1 workLanguage and Linguistics · 1 work

🧭 Topics 1Research subjects and languages the work is about.Information retrieval & search · 1 work

💡 Concepts 3Key ideas and methods explained on our concept pages.Natural language processing · 1 workQuestion answering · 1 workRetrieval-augmented generation · 1 work

 Works by year

2020s

20211 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (2020 · 6,256 citations)
    Large pre-trained language models store many facts in their weights, but they offer poor means of precisely accessing this knowledge, updating it, or showing where an answer came from.
  2. PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them (2021 · 288 citations)
    Open-domain QA systems that work directly with question-answer pairs, such as closed-book (CBQA) models and QA-pair retrievers, are fast, compact and easy to inspect and update.

All works

6 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. Retrieval-Augmented Generation for Knowledge-Intensive NLP TasksarXiv:2005.11401Patrick Lewis, Ethan Perez, Aleksandra Piktus, et al.2020 · 6,256 citations
  2. StarCraft II: A New Challenge for Reinforcement Learning ↗arXiv (Cornell University) · no summary yetOriol Vinyals et al.2017 · 680 citations
  3. PAQ: 65 Million Probably-Asked Questions and What You Can Do With ThemTransactions of the Association for Computational Linguistics (TACL)Patrick Lewis, Yuxiang Wu, Linqing Liu, et al.2021 · 288 citations
  4. DeepMind Lab ↗arXiv:1612.03801 · no summary yetCharles Beattie et al.2016 · 134 citations
  5. NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned ↗arXiv (Cornell University) · no summary yetSewon Min et al.2021 · 108 citations
  6. Kickstarting Deep Reinforcement Learning ↗arXiv (Cornell University) · no summary yetSimon Schmitt et al.2018 · 51 citations

 Co-authors here

12 of 14 co-authors with a page, the most papers together first.

Venues

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

 Cited by

Papers of our library cite their works 3,530 times (of the 149,439 papers whose bibliographies we read); 603 citing papers with a page here →.

Updated

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