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Tejaswini Pedapati

Tejaswini Pedapati has 2 papers in our library, in 2026, most of them on Language models & pretraining, Efficient models & compression; often with Dennis Wei, Elizabeth M. Daly, Erik Miehling.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 10 · 70 works · 577 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 2 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #11282

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

🏢IBMArmonk · United States2017–2026 · 49 paperscurrent🔬IBM Research - Thomas J. Watson Research CenterYorktown Heights · United States2017–2025 · 5 papers
🏛️Columbia University Columbia CollegeNew York · United States2012–2014Education 2012–2014 · Masters, Computer Science
🏛️IBM ResearchYorktown Heights · United States2014Employment since 2014 · Research Engineer

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workSafety Research · 1 workSocial Sciences · 1 work

🧭 Topics 2Research subjects and languages the work is about.Efficient models & compression · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. OjaKV: Context-Aware Online Low-Rank KV Cache Compression (2026 · 2 citations)
    Long-context LLM inference is limited by GPU memory for the key-value (KV) cache. For Llama-3.1-8B with a 32K-token prompt at batch size 4, the cache reaches about 16 GB, roughly the size of the model weights. Earlier low-rank compression methods project keys and values onto a fixed basis learned offline from…
  2. AI Steerability 360: A Toolkit for Steering Large Language Models (2026)
    Many techniques now exist for lightweight control of LLM behavior. Each follows its own conventions, so comparing or combining them is hard, and so is attributing effects to a specific intervention. IBM Research presents AI Steerability 360, an open-source, Hugging Face–native Python library (Apache 2.0). It groups…

All works

3 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. OjaKV: Context-Aware Online Low-Rank KV Cache CompressionFindings of the Association for Computational LinguisticsYuxuan Zhu, David H. Yang, Mohammad Mohammadi Amiri, et al.2026 · 2 citations
  2. AI Steerability 360: A Toolkit for Steering Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Erik Miehling, Karthikeyan Natesan Ramamurthy, Praveen Venkateswaran, et al.2026
  3. ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetDavid H. Yang et al.2026

 Co-authors here

8 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 2 times (of the 149,439 papers whose bibliographies we read).

Updated

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