collaborators

5 papers

cs.CL2026

Experiments or Outcomes? Probing Scientific Feasibility in Large Language Models

Seyedali Mohammadi, Manas Gaur, Francis Ferraro

Scientific feasibility assessment asks whether a claim is consistent with established knowledge and whether experimental evidence could support or refute it. We frame feasibility a…

cs.CL2026

Do LLMs Adhere to Label Definitions? Examining Their Receptivity to External Label Definitions

Seyedali Mohammadi, Bhaskara Hanuma Vedula, Hemank Lamba +4

Do LLMs genuinely incorporate external definitions, or do they primarily rely on their parametric knowledge? To address these questions, we conduct controlled experiments across mu…

cs.CL2026

LingVarBench: Benchmarking LLMs on Entity Recognitions and Linguistic Verbalization Patterns in Phone-Call Transcripts

Seyedali Mohammadi, Manas Paldhe, Amit Chhabra +2

We study structured entity extraction from phone-call transcripts in customer-support and healthcare settings, where annotation is costly, and data access is limited by privacy and…

cs.CL2025

Attribution in Scientific Literature: New Benchmark and Methods

Yash Saxena, Deepa Tilwani, Ali Mohammadi +4

Large language models (LLMs) present a promising yet challenging frontier for automated source citation in scientific communication. Previous approaches to citation generation have…

cs.CR2025

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation

Seyedreza Mohseni, Seyedali Mohammadi, Deepa Tilwani +5

Malware authors often employ code obfuscations to make their malware harder to detect. Existing tools for generating obfuscated code often require access to the original source cod…