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Kannan Ramchandran

Kannan Ramchandran has 2 papers in our library, in 2024–2025; often with Dan Klein, Joseph E. Gonzalez, Kangwook Lee.

2 papers in our library · 2024–2025

OpenAlex · ORCID · h-index 83 · 715 works · 30,746 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 88 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #8356

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 States1999–2026 · 430 paperscurrent🎓University of Illinois Urbana-ChampaignUrbana · United States1993–2007 · 95 papers🎓Columbia UniversityNew York · United States1992–2003 · 11 papers🎓University of Illinois SystemUrbana · United States1994–2002 · 6 papers🎓University of California San DiegoSan Diego · United States2021–2022 · 2 papers🎓Rice UniversityHouston · United States2018–2019 · 2 papers🎓University of Southern CaliforniaLos Angeles · United States1998–2010 · 2 papers🎓Princeton UniversityPrinceton · United States1999–2002 · 2 papers🎓University of California SystemOakland · United States2020 · 1 paperEmployment · professor, eecs

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 8 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 workLanguage and Linguistics · 1 workComputational Theory and Mathematics · 1 work

 Works by year

2020s

20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Why Do Multi-Agent LLM Systems Fail? (2025 · 89 citations)
    Multi-agent LLM systems (MAS) are popular, yet they often perform little better than single agents or simple baselines.
  2. Looped Transformers for Length Generalization (2024 · 13 citations)
    Transformers trained from scratch on arithmetic or algorithmic tasks usually fail on inputs longer than those seen during training, partly because their depth is fixed.

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. EC-cache: load-balanced, low-latency cluster caching with online erasure coding ↗Operating Systems Design and Implementation · no summary yetK. V. Rashmi et al.2016 · 98 citations
  2. Why Do Multi-Agent LLM Systems Fail?arXiv:2503.13657Mert Cemri, Melissa Z. Pan, Shuyi Yang, et al.2025 · 89 citations
  3. Looped Transformers for Length GeneralizationarXiv:2409.15647Ying Fan, Yilun Du, Kannan Ramchandran, et al.2024 · 13 citations
  4. Robust Class Parallelism - Error Resilient Parallel Inference with Low Communication Cost ↗2018 52nd Asilomar Conference on Signals, Systems, and Computers · no summary yetYaoqing Lamar Yang et al.2018 · 3 citations
  5. SkyDiscover: A Flexible, Adaptive Framework for AI-Driven Scientific and Algorithmic Discovery ↗no summary yetShu Liu et al.2026 · 2 citations

 Co-authors here

7 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 88 times (of the 149,439 papers whose bibliographies we read); 27 citing papers with a page here →.

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