--- title: "Daniel Guo — author profile and papers — Elamur Research" description: "Daniel Guo: 2 papers on Elamur Research (2020–2023), h-index 6 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/daniel-guo/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/daniel-guo/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Daniel Guo # Daniel Guo Daniel Guo has 2 papers in our library, in 2020–2023, most of them on [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Bilal Piot](https://md.research.elamur.ai/free/en/authors/bilal-piot/), [Charles Blundell](https://md.research.elamur.ai/free/en/authors/charles-blundell/), [Daniele Calandriello](https://md.research.elamur.ai/free/en/authors/daniele-calandriello/). 2 papers in our library · 2020–2023 [OpenAlex](https://openalex.org/A5102988656) · [**h-index 6**](https://openalex.org/authors/A5102988656) · [13 works](https://openalex.org/works?filter=author.id:A5102988656) · [549 citations](https://openalex.org/works?filter=author.id:A5102988656&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/daniel-guo/#papers) · [🔗 Cited 269 times in our library](https://md.research.elamur.ai/free/en/authors/daniel-guo/cited-by/) · [⭐ Paper Stars ranking: #4387](https://md.research.elamur.ai/free/en/paper-stars/page/44/#star-4387) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Daniel+Guo) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Daniel+Guo) · [dblp](https://dblp.org/search?q=Daniel+Guo) · [ACL Anthology](https://aclanthology.org/search/?q=Daniel+Guo) ## Affiliations [🎓**Stanford University** Stanford · United States 2024–2025 · 2 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 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 4 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Decision Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/) · [Management Science and Operations Research · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/management-science-and-operations-research/) 🧭 Topics 1 Research subjects and languages the work is about.[Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) ## Works by year ### 2020s [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/daniel-guo/year/2023/) · [**2020** 1 paper](https://md.research.elamur.ai/free/en/authors/daniel-guo/year/2020/) ## Papers The most cited first (OpenAlex and our library). 1. **[A General Theoretical Paradigm to Understand Learning from Human Preferences](https://md.research.elamur.ai/free/en/papers/azar-2023-general-theoretical-paradigm-understand-learning/)** *(2023 · 263 citations)* This paper by researchers at Google DeepMind provides a theoretical foundation for methods that train language models from human preferences. 2. **[Agent57: Outperforming the Atari Human Benchmark](https://md.research.elamur.ai/free/en/papers/badia-2020-agent57-outperforming-atari-human-benchmark/)** *(2020 · 235 citations)* The suite of 57 Atari 2600 games (the ALE environment) has served for about ten years as the standard test of how general reinforcement learning (RL) algorithms are. ## Co-authors here 7 co-authors with a page, the most papers together first. - [Bilal Piot](https://md.research.elamur.ai/free/en/authors/bilal-piot/) ×2 - [Charles Blundell](https://md.research.elamur.ai/free/en/authors/charles-blundell/) - [Daniele Calandriello](https://md.research.elamur.ai/free/en/authors/daniele-calandriello/) - [Mark Rowland](https://md.research.elamur.ai/free/en/authors/mark-rowland/) - [Michal Valko](https://md.research.elamur.ai/free/en/authors/michal-valko/) - [Mohammad Gheshlaghi Azar](https://md.research.elamur.ai/free/en/authors/mohammad-gheshlaghi-azar/) - [Rémi Munos](https://md.research.elamur.ai/free/en/authors/remi-munos/) ## Cited by Papers of our library cite their works 269 times (of the 149,439 papers whose bibliographies we read); [69 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/daniel-guo/cited-by/). Updated 3 November 2026