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Mark Russinovich

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CR2
  • cs.AI1
  • cs.CL1

identity via Semantic Scholar / OpenAlex

most citedWho's Harry Potter? Approximate Unlearning in LLMs

14 citations · 14 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AI2025

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs

Yanan Cai, Ahmed Salem, Besmira Nushi +1

We introduce LogiPlan, a novel benchmark designed to evaluate the capabilities of large language models (LLMs) in logical planning and reasoning over complex relational structures.…

cs.CR2025

LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection Challenge

Sahar Abdelnabi, Aideen Fay, Ahmed Salem +22

Indirect Prompt Injection attacks exploit the inherent limitation of Large Language Models (LLMs) to distinguish between instructions and data in their inputs. Despite numerous def…

cs.CR2023

Confidential Consortium Framework: Secure Multiparty Applications with Confidentiality, Integrity, and High Availability

Heidi Howard, Fritz Alder, Edward Ashton +12

Confidentiality, integrity protection, and high availability, abbreviated to CIA, are essential properties for trustworthy data systems. The rise of cloud computing and the growing…

cs.CL2023★ 14 cited

Who's Harry Potter? Approximate Unlearning in LLMs

Ronen Eldan, Mark Russinovich

Large language models (LLMs) are trained on massive internet corpora that often contain copyrighted content. This poses legal and ethical challenges for the developers and users of…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.