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Simeng Sun

Simeng Sun has 2 papers in our library, in 2021–2024, most of them on Language models & pretraining; often with Andrew Mattarella-Micke, Boris Ginsburg, Cheng-Ping Hsieh.

2 papers in our library · 2021–2024

OpenAlex · ORCID · h-index 14 · 43 works · 821 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 524 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #3404

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

🏛️Nanjing Municipal Center for Disease Control And PreventionNanjing · China2024–2026 · 2 paperscurrent🎓University of Massachusetts AmherstAmherst Center · United States2020–2024 · 19 papers🎓University of Science and Technology of ChinaHefei · China2019–2023 · 8 papers🏢MicrosoftRedmond · United States2023–2024 · 3 papers🏢MetaMenlo Park · United States2021–2023 · 3 papers🏢Adobe SystemsSan Jose · United States2021 · 2 papers🎓Beihang UniversityBeijing · China2017–2018 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 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).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 2 works

 Works by year

2020s

20241 paperSimeng Sun's papers of 202420211 paperSimeng Sun's papers of 2021

 Papers

The most cited first (OpenAlex and our library).

  1. RULER: What's the Real Context Size of Your Long-Context Language Models? (2024 · 386 citations)
    Long-context language models are usually checked with the needle-in-a-haystack (NIAH) test. That test only shows whether a model can find one planted fact, so it says little about deeper use of long inputs. The NVIDIA authors built RULER, a fully synthetic benchmark whose input length and difficulty can be set…
  2. Do Long-Range Language Models Actually Use Long-Range Context? (2021 · 100 citations)
    Long-range Transformer language models can now read thousands of tokens of preceding text, and they reach lower perplexity on benchmarks such as PG-19.

All works

5 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. RULER: What's the Real Context Size of Your Long-Context Language Models?arXiv:2404.06654Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.2024 · 386 citations
  2. TopicGPT: A Prompt-based Topic Modeling Framework ↗NAACL 2024 · no summary yetChau Minh Pham et al.2024 · 167 citations
  3. Do Long-Range Language Models Actually Use Long-Range Context?Conference on Empirical Methods in Natural Language Processing (EMNLP)Simeng Sun, Kalpesh Krishna, Andrew Mattarella-Micke, et al.2021 · 100 citations
  4. Suri: Multi-constraint Instruction Following in Long-form Text Generation ↗Findings of the Association for Computational Linguistics: EMNLP 2024 · no summary yetChau Minh Pham, Simeng Sun, Mohit Iyyer2024 · 18 citations
  5. Exploring the impact of low-rank adaptation on the performance, efficiency, and regularization of RLHF ↗arXiv:2309.09055 · no summary yetSimeng Sun, Dhawal Gupta, Mohit Iyyer2023 · 9 citations

 Co-authors here

6 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 524 times (of the 141,840 papers whose bibliographies we read); 31 citing papers with a page here →.

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