91 citations · 250 across the 37 of their papers we have counts for
Showing cs.AIShow all
2 papers · 1 filter
cs.AI2025
Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs
Mina Taraghi, Yann Pequignot, Amin Nikanjam +2
Organizations increasingly adapt Large Language Models (LLMs) from public repositories such as HuggingFace to downstream tasks. Prior work shows that even fine-tuning on benign dat…
cs.AI2025
Prism: Dynamic and Flexible Benchmarking of LLMs Code Generation with Monte Carlo Tree Search
Vahid Majdinasab, Amin Nikanjam, Foutse Khomh
The rapid advancement of Large Language Models (LLMs) has outpaced traditional evaluation methods. Static benchmarks fail to capture the depth and breadth of LLM capabilities and e…