2 citations · 2 across the 4 of their papers we have counts for
7 papers
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…
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…
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…
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…
IoT-Based Preventive Mental Health Using Knowledge Graphs and Standards for Better Well-Being
Amelie Gyrard, Seyedali Mohammadi, Manas Gaur +1
Sustainable Development Goals (SDGs) give the UN a road map for development with Agenda 2030 as a target. SDG3 "Good Health and Well-Being" ensures healthy lives and promotes well-…
WellDunn: On the Robustness and Explainability of Language Models and Large Language Models in Identifying Wellness Dimensions
Seyedali Mohammadi, Edward Raff, Jinendra Malekar +3
Language Models (LMs) are being proposed for mental health applications where the heightened risk of adverse outcomes means predictive performance may not be a sufficient litmus te…