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Anastasios N. Angelopoulos

Anastasios N. Angelopoulos has 2 papers in our library, in 2021–2024, most of them on Language models & pretraining, Dialogue systems, Evaluation & benchmarks; often with Banghua Zhu, Dacheng Li, Hao Zhang.

2 papers in our library · 2021–2024

OpenAlex · ORCID · Wikidata · h-index 18 · 62 works · 1,938 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 561 times in our library · 7 more in our library without a page yet · ⭐ Paper Stars ranking: #3727

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

🎓University of California, BerkeleyBerkeley · United States2019–2026 · 38 papersEmployment 2019–2024 · Electrical Engineering and Computer Sciencescurrent🏢OranoWashington D.C. · United States2026 · 1 papercurrent🎓Stanford UniversityStanford · United States2019–2020 · 3 papers
🏛️ArenaSan Francisco · United States2024Employment since 2024 · CEO

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.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksArts and Humanities · 1 workComputer Networks and Communications · 1 workLanguage and Linguistics · 1 work

🧭 Topics 3Research subjects and languages the work is about.Dialogue systems · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Chatbots · 1 work

 Works by year

2020s

20241 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference (2024 · 546 citations)
    The authors show that conventional LLM benchmarks poorly reflect how models are actually used. These are fixed sets of closed-ended questions with reference answers: over time they leak into training data, become saturated, and do not account for human preferences in open-ended tasks. As an alternative, they propose…
  2. A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification (2021 · 79 citations)
    Modern machine learning models that operate as a "black box" are increasingly deployed in high-stakes domains such as medicine.

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. Chatbot Arena: An Open Platform for Evaluating LLMs by Human PreferencearXiv:2403.04132Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.2024 · 546 citations
  2. A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty QuantificationarXiv:2107.07511Anastasios N. Angelopoulos, Stephen Bates2021 · 79 citations
  3. How to Evaluate Reward Models for RLHF ↗arXiv:2410.14872 · no summary yetEvan Frick et al.2024 · 31 citations
  4. Search Arena: Analyzing Search-Augmented LLMs ↗arXiv (Cornell University) · no summary yetMihran Miroyan et al.2025 · 11 citations
  5. Copilot Arena: A Platform for Code LLM Evaluation in the Wild ↗arXiv (Cornell University) · no summary yetWayne Chi et al.2025 · 9 citations
  6. Prompt-to-Leaderboard ↗arXiv (Cornell University) · no summary yetEvan Frick et al.2025 · 9 citations
  7. Specifications: The missing link to making the development of LLM systems an engineering discipline ↗arXiv (Cornell University) · no summary yetIon Gabriel Stoica et al.2024 · 4 citations
  8. EDIT-Bench: Evaluating LLM Abilities to Perform Real-World Instructed Code Edits ↗arXiv (Cornell University) · no summary yetWayne Chi et al.2025 · 2 citations
  9. Post-Training Frontier Text-to-Image Models by Composing Preference and Rubric Rewards ↗arXiv (Cornell University) · no summary yetYuanhao Ban et al.2026

 Co-authors here

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

 Cited by

Papers of our library cite their works 561 times (of the 149,439 papers whose bibliographies we read); 148 citing papers with a page here →.

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