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Aniruddha Nrusimha

Aniruddha Nrusimha has 2 papers in our library, in 2023–2024, most of them on Efficient models & compression; often with William Brandon, Mayank Mishra, Rameswar Panda.

2 papers in our library · 2023–2024

OpenAlex · h-index 4 · 13 works · 94 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 163 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #8449

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

🎓Stanford UniversityStanford · United States2026 · 1 papercurrent🎓Massachusetts Institute of TechnologyCambridge · United States2022–2025 · 4 papers🎓University of California, BerkeleyBerkeley · United States2021–2022 · 2 papers

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

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6The 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 worksHardware and Architecture · 1 work

🧭 Topics 1Research subjects and languages the work is about.Efficient models & compression · 1 work

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Reducing Transformer Key-Value Cache Size with Cross-Layer Attention (2024 · 57 citations)
    When large language models generate text autoregressively, they store keys and values (the KV cache) for every token and layer.
  2. Striped Attention: Faster Ring Attention for Causal Transformers (2023 · 41 citations)
    Ring Attention (Liu et al., 2023) makes very long contexts trainable by splitting queries, keys and values along the sequence across accelerators arranged in a ring.

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. Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization ↗MLSys 2020 · no summary yetParas Jain et al.2019 · 98 citations
  2. Reducing Transformer Key-Value Cache Size with Cross-Layer AttentionConference on Neural Information Processing Systems (NeurIPS)William Brandon, Mayank Mishra, Aniruddha Nrusimha, et al.2024 · 57 citations
  3. Striped Attention: Faster Ring Attention for Causal TransformersarXiv:2311.09431William Brandon, Aniruddha Nrusimha, Kevin Qian, et al.2023 · 41 citations
  4. Towards Verifiable Text Generation with Symbolic References ↗arXiv (Cornell University) · no summary yetLucas Torroba Hennigen et al.2023 · 10 citations
  5. Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization ↗arXiv:2404.03605 · no summary yetAniruddha Nrusimha et al.2024 · 6 citations
  6. FlashFormer: Whole-Model Kernels for Efficient Low-Batch Inference ↗arXiv (Cornell University) · no summary yetAniruddha Nrusimha et al.2025 · 3 citations

 Co-authors here

5 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 163 times (of the 149,439 papers whose bibliographies we read); 18 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/aniruddha-nrusimha/