2 citations · 2 across the 3 of their papers we have counts for
4 papers
Risk Management for Mitigating Benchmark Failure Modes: BenchRisk
Sean McGregor, Victor Lu, Vassil Tashev +8
Large language model (LLM) benchmarks inform LLM use decisions (e.g., "is this LLM safe to deploy for my use case and context?"). However, benchmarks may be rendered unreliable by…
Capturing the Effects of Quantization on Trojans in Code LLMs
Aftab Hussain, Sadegh AlMahdi Kazemi Zarkouei, Md Rafiqul Islam Rabin +3
Large language models of code exhibit high capability in performing diverse software engineering tasks, such as code translation, defect detection, text-to-code generation, and cod…
Search-Based Multi-Trajectory Refinement for Safe C-to-Rust Translation with Large Language Models
HoHyun Sim, Hyeonjoong Cho, Yeonghyeon Go +4
The C programming language has been foundational in building system-level software. However, its manual memory management model frequently leads to memory safety issues. In respons…
From Prompts to Propositions: A Logic-Based Lens on Student-LLM Interactions
Ali Alfageeh, Sadegh AlMahdi Kazemi Zarkouei, Daye Nam +9
Background and Context. The increasing integration of large language models (LLMs) in computing education presents an emerging challenge in understanding how students use LLMs and…