works on

From the 1 of 8 linked papers with an AI index.

collaborators

8 papers

cs.IT2026

Soft GRAND under Channel Switching and Drift

Behrooz Razeghi

Under channel switching or drift, the posterior used to order soft GRAND queries can differ from the matched correction posterior, which can increase rank and finite-budget decodin…

cs.IT2026

Tail-Calibrated Soft-Output GRAND for Finite-Memory Noise-Effect Posteriors

Behrooz Razeghi

In guessing random additive noise decoding (GRAND), memory in the hard-decision noise effect changes the likelihood order of candidate noise effects. In soft-output decoding, the s…

cs.IT2026

Low-Pathwidth GRAND: Exact Likelihood-Ordered Enumeration for BPSK Transmission over Correlated Gaussian Noise

Behrooz Razeghi

The paper introduces Low-Pathwidth GRAND (LP‑GRAND), an exact maximum‑likelihood decoding method for BPSK transmission over correlated Gaussian noise that exploits the low pathwidt…

cs.IR2026

ScoreShield: Differentially Private Release of Similarity Scores

Behrooz Razeghi, Parsa Rahimi

A growing number of applications, such as biometrics and retrieval-augmented generation (RAG), rely on cosine similarity scores computed between vector embeddings of text, images,…

cs.AI2026

Principles Do Not Apply Themselves: A Hermeneutic Perspective on AI Alignment

Behrooz Razeghi

AI alignment is often framed as the task of ensuring that an AI system follows a set of stated principles or human preferences, but general principles rarely determine their own ap…

cs.IT2026

On the Capacity of Distinguishable Synthetic Identity Generation under Face Verification

Behrooz Razeghi

We study how many synthetic identities can be generated so that a face verifier declares same-identity pairs as matches and different-identity pairs as non-matches at a fixed thres…