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Bhavya Kailkhura

Bhavya Kailkhura has 2 papers in our library, in 2024, most of them on Language models & pretraining; often with Arpit Bansal, Avi Schwarzschild, Jinghan Jia.

2 papers in our library · 2024

OpenAlex · ORCID · Wikidata · h-index 28 · 199 works · 3,354 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 356 times in our library · 7 more in our library without a page yet · ⭐ Paper Stars ranking: #8823

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

🔬Lawrence Livermore National LaboratoryLivermore · United States2016–2026 · 132 papersEmploymentcurrent🎓Syracuse UniversitySyracuse · United States2013–2022 · 28 papersEducation🎓Michigan State UniversityEast Lansing · United States2023–2024 · 3 papers🎓ETH ZurichZurich · Switzerland2020 · 2 papers

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 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20242 papers

 Papers

The most cited first (OpenAlex and our library).

  1. SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning (2024 · 46 citations)
    The paper addresses LLM unlearning: removing the effect of unwanted data, such as private, copyrighted or toxic content, without full retraining and without harming general utility.
  2. Transformers Can Do Arithmetic with the Right Embeddings (2024 · 36 citations)
    Transformers often fail at multi-digit arithmetic. The authors argue the main cause is that the model cannot reliably tell where each digit sits inside a long number. They propose Abacus Embeddings , learned positional embeddings that index every digit by its offset from the start of its number, so digits of equal…

All works

9 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. Anomalous Example Detection in Deep Learning: A Survey ↗IEEE Access · no summary yetSaikiran Bulusu et al.2020 · 193 citations
  2. SOUL: Unlocking the Power of Second-Order Optimization for LLM UnlearningConference on Empirical Methods in Natural Language Processing (EMNLP)Jinghan Jia, Yihua Zhang, Yimeng Zhang, et al.2024 · 46 citations
  3. Transformers Can Do Arithmetic with the Right EmbeddingsConference on Neural Information Processing Systems (NeurIPS)Sean McLeish, Arpit Bansal, Alex Stein, et al.2024 · 36 citations
  4. Scalability vs. Utility: Do We Have to Sacrifice One for the Other in Data Importance Quantification? ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetRuoxi Jia et al.2019 · 33 citations
  5. GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations ↗arXiv (Cornell University) · no summary yetJinhao Duan et al.2024 · 27 citations
  6. Anomalous Instance Detection in Deep Learning: A Survey. ↗arXiv (Cornell University) · no summary yetSaikiran Bulusu et al.2020 · 27 citations
  7. GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations ↗neural information processing systems · no summary yetJinhao Duan et al.2024 · 23 citations
  8. Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression ↗arXiv (Cornell University) · no summary yetJunyuan Hong et al.2024 · 23 citations
  9. The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text ↗neural information processing systems · no summary yetNikhil Kandpal et al.2025 · 21 citations

 Co-authors here

10 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 356 times (of the 149,439 papers whose bibliographies we read); 87 citing papers with a page here →.

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