SABER: Scaling-Aware Best-of-N Estimation of Risk
Scaling-Aware Best-of-N Estimation of Risk A Python package for predicting large-scale adversarial risk in Large Language Models under Best-of-N sampling. Paper: https://arxiv.org/pdf/2601.22636 (opens in new tab) Standard LLM safety evaluations use single-shot (ASR@1) metrics,…
CROSS — Leveraging AI ASICs for Homomorphic Encryption
Artificial Intelligence (AI) is driving a new industrial revolution, transforming human workflows increasingly into digital tokens, i.e., tokenizing the entire world. However, this transformation exposes sensitive data at an unprecedented scale, leading to heavy privacy…
Research Intern – AI Safety and Security
Protecting large language models (LLMs) from malicious inputs is critical. LLMs can also be used to protect users from malicious attacks. The Deep Learning Team in Microsoft Research – Redmond is seeking Research Interns interested…
Hardware Realization and Implementation Security Evaluation of HQC, A NIST PQC Standard
Quantum computing is no longer a distant dream, its rapid progress is poised to revolutionize various fields from drug discovery to optimization. But this leap forward comes with a critical caveat: the pre-quantum public-key cryptographic…
Research Intern – Cryptography and Applications
As a Research Intern in the Strategic Planning and Architecture (SPARC) group, you will contribute to the research, design, and development of cryptos & crypto applications for Caliptra and its usage models. This role encompasses…
Media Authenticity Methods in Practice: Capabilities, Limitations, and Directions
As synthetic media grows, verifying what’s real, and the origin of content, matters more than ever. Our latest report explores media integrity and authentication methods, their limits, and practical paths toward trustworthy provenance across images,…