36 citations · 42 across the 9 of their papers we have counts for
3 papers · 1 filter
Generation-Time vs. Post-hoc Citation: A Holistic Evaluation of LLM Attribution
Yash Saxena, Raviteja Bommireddy, Ankur Padia +1
Trustworthy Large Language Models (LLMs) must cite human-verifiable sources in high-stakes domains such as healthcare, law, academia, and finance, where even small errors can have…
Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains
Yash Saxena, Ankur Padia, Mandar S Chaudhary +3
Retrieval-Augmented Generation (RAG) systems deployed in sensitive domains must provide interpretable evidence selection and robust safeguards against data poisoning, yet current a…
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…