🧑‍🔬 Rameswar Panda

🏛️ Affiliations

🏢IBMArmonk · United States2019–2026 · 69 paperscurrent🎓Massachusetts Institute of TechnologyCambridge · United States2019–2026 · 22 paperscurrent🎓University of California, RiversideRiverside · United States2015–2021 · 37 papers🎓Jadavpur UniversityKolkata · India2012–2017 · 5 papers🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2024 · 2 papers🎓Riverside City CollegeRiverside · United States2017–2018 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

🧭 Fields, topics and concepts

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

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Data Engineering for Scaling Language Models to 128K Context (2024 · 109 citations)
   Open-source LLMs that claim support for 100K+ tokens often fail the Needle-in-a-Haystack test, which checks whether a model can recall a fact hidden anywhere in a very long document.
2. 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.

All works

17 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. CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetChun-Fu Richard Chen, Quanfu Fan, Rameswar Panda2021 · 2,131 citations
2. CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual Learning ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetJames Seale Smith et al.2023 · 352 citations
3. Gated Linear Attention Transformers with Hardware-Efficient Training ↗arXiv:2312.06635 · no summary yetSonglin Yang et al.2023 · 138 citations
4. Data Engineering for Scaling Language Models to 128K ContextarXiv:2402.10171Yao Fu, Rameswar Panda, Xinyao Niu, et al.2024 · 109 citations
5. Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetBrian Chen et al.2021 · 78 citations
6. Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning ↗arXiv (Cornell University) · no summary yetZhen Wang et al.2023 · 77 citations
7. Collaborative Summarization of Topic-Related Videos ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetRameswar Panda, Amit K. Roy–Chowdhury2017 · 72 citations
8. AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetRameswar Panda et al.2021 · 60 citations
9. VALHALLA: Visual Hallucination for Machine Translation ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetYi Li et al.2022 · 58 citations
10. 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
11. LangNav: Language as a Perceptual Representation for Navigation ↗Findings of the Association for Computational Linguistics: NAACL 2024 · no summary yetBowen Pan et al.2024 · 32 citations
12. Learning to Grow Pretrained Models for Efficient Transformer Training ↗arXiv (Cornell University) · no summary yetPeihao Wang et al.2023 · 28 citations
13. ConStruct-VL: Data-Free Continual Structured VL Concepts Learning* ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetJames Seale Smith et al.2023 · 18 citations
14. Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models ↗arXiv:2404.05567 · no summary yetBowen Pan et al.2024 · 14 citations
15. Diversity Measurement and Subset Selection for Instruction Tuning Datasets ↗arXiv (Cornell University) · no summary yetPeiqi Wang et al.2024 · 10 citations
16. 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
17. FlashFormer: Whole-Model Kernels for Efficient Low-Batch Inference ↗arXiv (Cornell University) · no summary yetAniruddha Nrusimha et al.2025 · 3 citations

🤝 Co-authors here

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

• Aniruddha Nrusimha
• Hannaneh Hajishirzi
• Hao Peng
• Mayank Mishra
• William Brandon
• Xiang Yue
• Xinyao Niu
• Yao Fu
• Yoon Kim

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings ×4
• IEEE/CVF International Conference on Computer Vision (ICCV) ×3
• Conference on Neural Information Processing Systems (NeurIPS): NeurIPS 2024
• Findings of the Association for Computational Linguistics: NAACL 2024

🔗 Cited by

Papers of our library cite their works 539 times (of the 149,439 papers whose bibliographies we read); 118 citing papers with a page here →.

Updated 3 November 2026

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